From 64cfe672d6f9fbdafa5ea392693539ece301122e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Andr=C3=A9=20Anjos?= <andre.anjos@idiap.ch>
Date: Tue, 9 Jul 2024 21:05:56 +0000
Subject: [PATCH] Simplify package organisation
---
doc/api.rst | 232 +++++------
doc/cli.rst | 2 +-
doc/config.rst | 267 +++++++------
doc/contribute.rst | 2 +-
doc/data-model.rst | 6 +-
doc/install.rst | 51 ++-
doc/results/index.rst | 36 +-
doc/usage/evaluation.rst | 19 +-
doc/usage/experiment.rst | 27 +-
doc/usage/index.rst | 14 +-
doc/usage/saliency.rst | 88 +++--
doc/usage/training.rst | 11 +-
helpers/extract_hdf5_images.py | 3 +
helpers/gen_histograms.sh | 43 --
helpers/generate_histograms.py | 100 +++--
helpers/generate_histograms.sh | 48 +++
helpers/generate_histograms_classification.py | 307 --------------
helpers/generate_histograms_segmentation.py | 308 ---------------
helpers/montgomery_preprocess.py | 4 +-
helpers/tbx11k_make_splits.py | 7 +-
helpers/visceral_preprocess.py | 15 +-
pyproject.toml | 374 +++++++++---------
.../{libs/classification => }/__init__.py | 0
.../config => classify}/__init__.py | 0
.../data => classify/config}/__init__.py | 0
.../config/data}/__init__.py | 0
.../config/data/hivtb}/__init__.py | 0
.../config/data/hivtb/datamodule.py | 25 +-
.../config/data/hivtb/fold-0.json | 0
.../config/data/hivtb/fold-1.json | 0
.../config/data/hivtb/fold-2.json | 0
.../config/data/hivtb/fold-3.json | 0
.../config/data/hivtb/fold-4.json | 0
.../config/data/hivtb/fold-5.json | 0
.../config/data/hivtb/fold-6.json | 0
.../config/data/hivtb/fold-7.json | 0
.../config/data/hivtb/fold-8.json | 0
.../config/data/hivtb/fold-9.json | 0
.../config/data/hivtb/fold_0.py | 5 +-
.../config/data/hivtb/fold_1.py | 5 +-
.../config/data/hivtb/fold_2.py | 5 +-
.../config/data/hivtb/fold_3.py | 5 +-
.../config/data/hivtb/fold_4.py | 5 +-
.../config/data/hivtb/fold_5.py | 5 +-
.../config/data/hivtb/fold_6.py | 5 +-
.../config/data/hivtb/fold_7.py | 5 +-
.../config/data/hivtb/fold_8.py | 5 +-
.../config/data/hivtb/fold_9.py | 5 +-
.../config/data/indian}/__init__.py | 0
.../config/data/indian/datamodule.py | 8 +-
.../config/data/indian/default.json | 0
.../config/data/indian/default.py | 4 +-
.../config/data/indian/fold-0.json | 0
.../config/data/indian/fold-1.json | 0
.../config/data/indian/fold-2.json | 0
.../config/data/indian/fold-3.json | 0
.../config/data/indian/fold-4.json | 0
.../config/data/indian/fold-5.json | 0
.../config/data/indian/fold-6.json | 0
.../config/data/indian/fold-7.json | 0
.../config/data/indian/fold-8.json | 0
.../config/data/indian/fold-9.json | 0
.../config/data/indian/fold_0.py | 5 +-
.../config/data/indian/fold_1.py | 5 +-
.../config/data/indian/fold_2.py | 5 +-
.../config/data/indian/fold_3.py | 5 +-
.../config/data/indian/fold_4.py | 5 +-
.../config/data/indian/fold_5.py | 5 +-
.../config/data/indian/fold_6.py | 5 +-
.../config/data/indian/fold_7.py | 5 +-
.../config/data/indian/fold_8.py | 5 +-
.../config/data/indian/fold_9.py | 5 +-
.../config/data/montgomery}/__init__.py | 0
.../config/data/montgomery/datamodule.py | 25 +-
.../config/data/montgomery/default.json | 0
.../config/data/montgomery/default.py | 6 +-
.../config/data/montgomery/fold-0.json | 0
.../config/data/montgomery/fold-1.json | 0
.../config/data/montgomery/fold-2.json | 0
.../config/data/montgomery/fold-3.json | 0
.../config/data/montgomery/fold-4.json | 0
.../config/data/montgomery/fold-5.json | 0
.../config/data/montgomery/fold-6.json | 0
.../config/data/montgomery/fold-7.json | 0
.../config/data/montgomery/fold-8.json | 0
.../config/data/montgomery/fold-9.json | 0
.../config/data/montgomery/fold_0.py | 8 +-
.../config/data/montgomery/fold_1.py | 8 +-
.../config/data/montgomery/fold_2.py | 8 +-
.../config/data/montgomery/fold_3.py | 8 +-
.../config/data/montgomery/fold_4.py | 8 +-
.../config/data/montgomery/fold_5.py | 8 +-
.../config/data/montgomery/fold_6.py | 8 +-
.../config/data/montgomery/fold_7.py | 8 +-
.../config/data/montgomery/fold_8.py | 9 +-
.../config/data/montgomery/fold_9.py | 9 +-
.../data/montgomery_shenzhen}/__init__.py | 0
.../data/montgomery_shenzhen/datamodule.py | 10 +-
.../data/montgomery_shenzhen/default.py | 6 +-
.../config/data/montgomery_shenzhen/fold_0.py | 8 +-
.../config/data/montgomery_shenzhen/fold_1.py | 8 +-
.../config/data/montgomery_shenzhen/fold_2.py | 8 +-
.../config/data/montgomery_shenzhen/fold_3.py | 8 +-
.../config/data/montgomery_shenzhen/fold_4.py | 8 +-
.../config/data/montgomery_shenzhen/fold_5.py | 8 +-
.../config/data/montgomery_shenzhen/fold_6.py | 8 +-
.../config/data/montgomery_shenzhen/fold_7.py | 8 +-
.../config/data/montgomery_shenzhen/fold_8.py | 8 +-
.../config/data/montgomery_shenzhen/fold_9.py | 8 +-
.../montgomery_shenzhen_indian}/__init__.py | 0
.../montgomery_shenzhen_indian/datamodule.py | 10 +-
.../montgomery_shenzhen_indian/default.py | 7 +-
.../data/montgomery_shenzhen_indian/fold_0.py | 9 +-
.../data/montgomery_shenzhen_indian/fold_1.py | 8 +-
.../data/montgomery_shenzhen_indian/fold_2.py | 9 +-
.../data/montgomery_shenzhen_indian/fold_3.py | 9 +-
.../data/montgomery_shenzhen_indian/fold_4.py | 9 +-
.../data/montgomery_shenzhen_indian/fold_5.py | 9 +-
.../data/montgomery_shenzhen_indian/fold_6.py | 9 +-
.../data/montgomery_shenzhen_indian/fold_7.py | 8 +-
.../data/montgomery_shenzhen_indian/fold_8.py | 9 +-
.../data/montgomery_shenzhen_indian/fold_9.py | 8 +-
.../__init__.py | 0
.../datamodule.py | 10 +-
.../default.py | 2 +-
.../__init__.py | 0
.../datamodule.py | 10 +-
.../v1_fold_0.py | 2 +-
.../v1_fold_1.py | 2 +-
.../v1_fold_2.py | 2 +-
.../v1_fold_3.py | 2 +-
.../v1_fold_4.py | 2 +-
.../v1_fold_5.py | 2 +-
.../v1_fold_6.py | 2 +-
.../v1_fold_7.py | 2 +-
.../v1_fold_8.py | 2 +-
.../v1_fold_9.py | 2 +-
.../v1_healthy_vs_atb.py | 2 +-
.../v2_fold_0.py | 2 +-
.../v2_fold_1.py | 2 +-
.../v2_fold_2.py | 2 +-
.../v2_fold_3.py | 2 +-
.../v2_fold_4.py | 2 +-
.../v2_fold_5.py | 2 +-
.../v2_fold_6.py | 2 +-
.../v2_fold_7.py | 2 +-
.../v2_fold_8.py | 2 +-
.../v2_fold_9.py | 2 +-
.../v2_others_vs_atb.py | 2 +-
.../config/data/nih_cxr14}/__init__.py | 0
.../config/data/nih_cxr14/cardiomegaly.json | 0
.../config/data/nih_cxr14/cardiomegaly.py | 6 +-
.../config/data/nih_cxr14/datamodule.py | 23 +-
.../config/data/nih_cxr14/default.json.bz2 | Bin
.../config/data/nih_cxr14/default.py | 6 +-
.../data/nih_cxr14_padchest}/__init__.py | 0
.../data/nih_cxr14_padchest/datamodule.py | 6 +-
.../config/data/nih_cxr14_padchest/idiap.py | 2 +-
.../config/data/padchest}/__init__.py | 0
.../data/padchest/cardiomegaly-idiap.json | 0
.../data/padchest/cardiomegaly_idiap.py | 6 +-
.../config/data/padchest/datamodule.py | 25 +-
.../config/data/padchest/idiap.json.bz2 | Bin
.../config/data/padchest/idiap.py | 6 +-
.../config/data/padchest/no-tb-idiap.json.bz2 | Bin
.../config/data/padchest/no_tb_idiap.py | 4 +-
.../config/data/padchest/tb-idiap.json | 0
.../config/data/padchest/tb_idiap.py | 6 +-
.../config/data/shenzhen}/__init__.py | 0
.../config/data/shenzhen/alltest.json | 0
.../config/data/shenzhen/alltest.py | 6 +-
.../config/data/shenzhen/datamodule.py | 25 +-
.../config/data/shenzhen/default.json | 0
.../config/data/shenzhen/default.py | 6 +-
.../config/data/shenzhen/fold-0.json | 0
.../config/data/shenzhen/fold-1.json | 0
.../config/data/shenzhen/fold-2.json | 0
.../config/data/shenzhen/fold-3.json | 0
.../config/data/shenzhen/fold-4.json | 0
.../config/data/shenzhen/fold-5.json | 0
.../config/data/shenzhen/fold-6.json | 0
.../config/data/shenzhen/fold-7.json | 0
.../config/data/shenzhen/fold-8.json | 0
.../config/data/shenzhen/fold-9.json | 0
.../config/data/shenzhen/fold_0.py | 6 +-
.../config/data/shenzhen/fold_1.py | 6 +-
.../config/data/shenzhen/fold_2.py | 6 +-
.../config/data/shenzhen/fold_3.py | 6 +-
.../config/data/shenzhen/fold_4.py | 6 +-
.../config/data/shenzhen/fold_5.py | 6 +-
.../config/data/shenzhen/fold_6.py | 6 +-
.../config/data/shenzhen/fold_7.py | 6 +-
.../config/data/shenzhen/fold_8.py | 6 +-
.../config/data/shenzhen/fold_9.py | 6 +-
.../config/data/tbpoc}/__init__.py | 0
.../config/data/tbpoc/datamodule.py | 21 +-
.../config/data/tbpoc/fold-0.json | 0
.../config/data/tbpoc/fold-1.json | 0
.../config/data/tbpoc/fold-2.json | 0
.../config/data/tbpoc/fold-3.json | 0
.../config/data/tbpoc/fold-4.json | 0
.../config/data/tbpoc/fold-5.json | 0
.../config/data/tbpoc/fold-6.json | 0
.../config/data/tbpoc/fold-7.json | 0
.../config/data/tbpoc/fold-8.json | 0
.../config/data/tbpoc/fold-9.json | 0
.../config/data/tbpoc/fold_0.py | 4 +-
.../config/data/tbpoc/fold_1.py | 4 +-
.../config/data/tbpoc/fold_2.py | 4 +-
.../config/data/tbpoc/fold_3.py | 4 +-
.../config/data/tbpoc/fold_4.py | 4 +-
.../config/data/tbpoc/fold_5.py | 4 +-
.../config/data/tbpoc/fold_6.py | 4 +-
.../config/data/tbpoc/fold_7.py | 6 +-
.../config/data/tbpoc/fold_8.py | 6 +-
.../config/data/tbpoc/fold_9.py | 6 +-
.../config/data/tbx11k}/__init__.py | 0
.../config/data/tbx11k/datamodule.py | 14 +-
.../config/data/tbx11k/v1-fold-0.json | 0
.../config/data/tbx11k/v1-fold-1.json | 0
.../config/data/tbx11k/v1-fold-2.json | 0
.../config/data/tbx11k/v1-fold-3.json | 0
.../config/data/tbx11k/v1-fold-4.json | 0
.../config/data/tbx11k/v1-fold-5.json | 0
.../config/data/tbx11k/v1-fold-6.json | 0
.../config/data/tbx11k/v1-fold-7.json | 0
.../config/data/tbx11k/v1-fold-8.json | 0
.../config/data/tbx11k/v1-fold-9.json | 0
.../config/data/tbx11k/v1-healthy-vs-atb.json | 0
.../config/data/tbx11k/v1_fold_0.py | 4 +-
.../config/data/tbx11k/v1_fold_1.py | 4 +-
.../config/data/tbx11k/v1_fold_2.py | 4 +-
.../config/data/tbx11k/v1_fold_3.py | 4 +-
.../config/data/tbx11k/v1_fold_4.py | 4 +-
.../config/data/tbx11k/v1_fold_5.py | 6 +-
.../config/data/tbx11k/v1_fold_6.py | 6 +-
.../config/data/tbx11k/v1_fold_7.py | 4 +-
.../config/data/tbx11k/v1_fold_8.py | 6 +-
.../config/data/tbx11k/v1_fold_9.py | 4 +-
.../config/data/tbx11k/v1_healthy_vs_atb.py | 4 +-
.../config/data/tbx11k/v2-fold-0.json | 0
.../config/data/tbx11k/v2-fold-1.json | 0
.../config/data/tbx11k/v2-fold-2.json | 0
.../config/data/tbx11k/v2-fold-3.json | 0
.../config/data/tbx11k/v2-fold-4.json | 0
.../config/data/tbx11k/v2-fold-5.json | 0
.../config/data/tbx11k/v2-fold-6.json | 0
.../config/data/tbx11k/v2-fold-7.json | 0
.../config/data/tbx11k/v2-fold-8.json | 0
.../config/data/tbx11k/v2-fold-9.json | 0
.../config/data/tbx11k/v2-others-vs-atb.json | 0
.../config/data/tbx11k/v2_fold_0.py | 4 +-
.../config/data/tbx11k/v2_fold_1.py | 4 +-
.../config/data/tbx11k/v2_fold_2.py | 4 +-
.../config/data/tbx11k/v2_fold_3.py | 4 +-
.../config/data/tbx11k/v2_fold_4.py | 4 +-
.../config/data/tbx11k/v2_fold_5.py | 4 +-
.../config/data/tbx11k/v2_fold_6.py | 4 +-
.../config/data/tbx11k/v2_fold_7.py | 4 +-
.../config/data/tbx11k/v2_fold_8.py | 4 +-
.../config/data/tbx11k/v2_fold_9.py | 6 +-
.../config/data/tbx11k/v2_others_vs_atb.py | 4 +-
.../config/data/visceral}/__init__.py | 0
.../config/data/visceral/datamodule.py | 14 +-
.../config/data/visceral/default.json | 0
.../config/data/visceral/default.py | 4 +-
.../config/models}/__init__.py | 0
.../config/models/alexnet.py | 11 +-
.../config/models/alexnet_pretrained.py | 11 +-
.../config/models/cnn3d.py | 3 +-
.../config/models/densenet.py | 11 +-
.../config/models/densenet_pretrained.py | 11 +-
.../config/models/densenet_rs.py | 11 +-
.../config/models/logistic_regression.py | 4 +-
.../config/models/mlp.py | 2 +-
.../config/models/pasa.py | 9 +-
.../engine => classify/data}/__init__.py | 0
.../data/typing.py | 13 +-
.../saliency => classify/engine}/__init__.py | 0
.../engine/evaluator.py | 6 +-
.../engine/predictor.py | 2 +-
.../engine/saliency}/__init__.py | 0
.../engine/saliency/completeness.py | 4 +-
.../engine/saliency/evaluator.py | 0
.../engine/saliency/generator.py | 2 +-
.../engine/saliency/interpretability.py | 0
.../engine/saliency/viewer.py | 0
.../scripts => classify/models}/__init__.py | 0
.../models/alexnet.py | 2 +-
.../models/classification_model.py | 5 +-
.../models/cnn3d.py | 2 +-
.../models/densenet.py | 2 +-
.../models/logistic_regression.py | 0
.../models/loss_weights.py | 3 +-
.../classification => classify}/models/mlp.py | 0
.../models/normalizer.py | 0
.../models/pasa.py | 2 +-
.../models/typing.py | 0
.../saliency => classify/scripts}/__init__.py | 0
src/mednet/classify/scripts/cli.py | 44 +++
.../scripts/evaluate.py | 13 +-
.../scripts/saliency}/__init__.py | 0
.../scripts/saliency/completeness.py | 28 +-
.../scripts/saliency/evaluate.py | 4 +-
.../scripts/saliency/generate.py | 53 +--
.../scripts/saliency/interpretability.py | 11 +-
.../scripts/saliency/view.py | 5 +-
.../{libs/common => config}/__init__.py | 0
.../augmentations}/__init__.py | 0
.../config/augmentations/affine.py | 0
.../config/augmentations/elastic.py | 8 +-
.../common => }/config/augmentations/hflip.py | 0
.../config/augmentations/hflip_affine.py | 0
.../augmentations/hflip_jitter_affine.py | 0
.../config/augmentations/jitter.py | 0
src/mednet/{libs/common => }/data/__init__.py | 0
.../{libs/common => }/data/augmentations.py | 0
.../{libs/common => }/data/datamodule.py | 5 +
.../{libs/common => }/data/image_utils.py | 0
src/mednet/{libs/common => }/data/split.py | 3 +-
src/mednet/{libs/common => }/data/typing.py | 0
.../augmentations => engine}/__init__.py | 0
.../{libs/common => }/engine/callbacks.py | 0
src/mednet/{libs/common => }/engine/device.py | 0
.../{libs/common => }/engine/loggers.py | 0
.../{libs/common => }/engine/trainer.py | 123 ++++++
src/mednet/engine/uploader.py | 345 ++++++++++++++++
src/mednet/libs/classification/scripts/cli.py | 76 ----
.../libs/classification/scripts/config.py | 107 -----
.../libs/classification/scripts/database.py | 131 ------
.../libs/classification/scripts/experiment.py | 161 --------
.../libs/classification/scripts/predict.py | 80 ----
.../libs/classification/scripts/train.py | 130 ------
.../libs/classification/scripts/upload.py | 79 ----
.../libs/classification/utils/gitlab.py | 90 -----
src/mednet/libs/common/scripts/database.py | 102 -----
src/mednet/libs/common/scripts/predict.py | 165 --------
src/mednet/libs/common/scripts/upload.py | 220 -----------
src/mednet/libs/common/utils/gitlab.py | 90 -----
src/mednet/libs/segmentation/scripts/cli.py | 49 ---
src/mednet/libs/segmentation/scripts/click.py | 28 --
.../libs/segmentation/scripts/config.py | 107 -----
.../libs/segmentation/scripts/database.py | 130 ------
.../libs/segmentation/scripts/predict.py | 81 ----
src/mednet/libs/segmentation/scripts/train.py | 109 -----
.../libs/segmentation/scripts/upload.py | 78 ----
.../common/engine => models}/__init__.py | 0
.../{libs/common => }/models/loss_weights.py | 0
src/mednet/{libs/common => }/models/model.py | 2 +-
.../{libs/common => }/models/transforms.py | 0
src/mednet/{libs/common => }/models/typing.py | 0
src/mednet/scripts/cli.py | 31 +-
src/mednet/{libs/common => }/scripts/click.py | 0
.../{libs/common => }/scripts/config.py | 116 +++++-
src/mednet/scripts/database.py | 222 +++++++++++
.../segmentation => }/scripts/experiment.py | 42 +-
src/mednet/scripts/info.py | 54 +--
src/mednet/scripts/predict.py | 188 +++++++++
src/mednet/{libs/common => }/scripts/train.py | 192 +++++----
.../common => }/scripts/train_analysis.py | 3 +-
src/mednet/scripts/upload.py | 128 ++++++
src/mednet/{libs/common => }/scripts/utils.py | 23 +-
.../common/models => segment}/__init__.py | 0
.../scripts => segment/config}/__init__.py | 0
.../utils => segment/config/data}/__init__.py | 0
.../config/data/avdrive}/__init__.py | 0
.../config/data/avdrive/datamodule.py | 16 +-
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.../config/data/avdrive/default.py | 2 +-
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.../config/data/chasedb1/datamodule.py | 16 +-
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.../config/data/chasedb1/first_annotator.py | 2 +-
.../config/data/chasedb1/masks/Image_01L.png | Bin
.../config/data/chasedb1/masks/Image_01R.png | Bin
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.../config/data/chasedb1/masks/Image_03R.png | Bin
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.../config/data/chasedb1/masks/Image_04R.png | Bin
.../config/data/chasedb1/masks/Image_05L.png | Bin
.../config/data/chasedb1/masks/Image_05R.png | Bin
.../config/data/chasedb1/masks/Image_06L.png | Bin
.../config/data/chasedb1/masks/Image_06R.png | Bin
.../config/data/chasedb1/masks/Image_07L.png | Bin
.../config/data/chasedb1/masks/Image_07R.png | Bin
.../config/data/chasedb1/masks/Image_08L.png | Bin
.../config/data/chasedb1/masks/Image_08R.png | Bin
.../config/data/chasedb1/masks/Image_09L.png | Bin
.../config/data/chasedb1/masks/Image_09R.png | Bin
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.../config/data/chasedb1/masks/Image_10R.png | Bin
.../config/data/chasedb1/masks/Image_11L.png | Bin
.../config/data/chasedb1/masks/Image_11R.png | Bin
.../config/data/chasedb1/masks/Image_12L.png | Bin
.../config/data/chasedb1/masks/Image_12R.png | Bin
.../config/data/chasedb1/masks/Image_13L.png | Bin
.../config/data/chasedb1/masks/Image_13R.png | Bin
.../config/data/chasedb1/masks/Image_14L.png | Bin
.../config/data/chasedb1/masks/Image_14R.png | Bin
.../data/chasedb1/second-annotator.json | 0
.../config/data/chasedb1/second_annotator.py | 2 +-
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.../config/models/lwnet.py | 15 +-
.../config/models/m2unet.py | 15 +-
.../config/models/unet.py | 15 +-
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.../engine/evaluator.py | 22 +-
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.../models/driu_pix.py | 2 +-
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.../models/segmentation_model.py | 7 +-
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src/mednet/segment/scripts/cli.py | 28 ++
.../scripts/dump_annotations.py | 28 +-
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.../segmentation/models => utils}/__init__.py | 0
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.../{classification => classify}/test_cli.py | 124 +-----
.../test_evaluator.py | 22 +-
.../test_hivtb.py | 10 +-
.../test_indian.py | 10 +-
.../test_montgomery.py | 16 +-
.../test_montgomery_shenzhen.py | 12 +-
.../test_montgomery_shenzhen_indian.py | 16 +-
...est_montgomery_shenzhen_indian_padchest.py | 20 +-
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.../test_saliencymap_interpretability.py | 4 +-
.../test_shenzhen.py | 10 +-
.../test_summary.py | 4 +-
.../test_tbpoc.py | 16 +-
.../test_tbx11k.py | 10 +-
.../test_visceral.py | 6 +-
tests/conftest.py | 12 +-
.../scripts => tests/segment}/__init__.py | 0
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.../test_chasedb1.py | 39 +-
tests/{segmentation => segment}/test_cli.py | 114 ++----
tests/{segmentation => segment}/test_cxr8.py | 14 +-
.../{segmentation => segment}/test_drhagis.py | 14 +-
.../test_drionsdb.py | 41 +-
.../test_drishtigs1.py | 14 +-
tests/{segmentation => segment}/test_drive.py | 14 +-
tests/{segmentation => segment}/test_hrf.py | 35 +-
.../{segmentation => segment}/test_iostar.py | 14 +-
tests/{segmentation => segment}/test_jsrt.py | 43 +-
.../test_measures.py | 2 +-
.../test_montgomery.py | 14 +-
.../{segmentation => segment}/test_refuge.py | 28 +-
.../test_rimoner3.py | 14 +-
.../test_shenzhen.py | 14 +-
tests/{segmentation => segment}/test_stare.py | 33 +-
tests/segmentation/__init__.py | 0
tests/test_cli.py | 95 ++++-
tests/test_database_split.py | 2 +-
tests/test_image_utils.py | 2 +-
tests/test_resource_monitor.py | 38 +-
tests/test_transforms.py | 4 +-
2197 files changed, 3294 insertions(+), 4840 deletions(-)
delete mode 100755 helpers/gen_histograms.sh
create mode 100755 helpers/generate_histograms.sh
delete mode 100644 helpers/generate_histograms_classification.py
delete mode 100644 helpers/generate_histograms_segmentation.py
rename src/mednet/{libs/classification => }/__init__.py (100%)
rename src/mednet/{libs/classification/config => classify}/__init__.py (100%)
rename src/mednet/{libs/classification/config/data => classify/config}/__init__.py (100%)
rename src/mednet/{libs/classification/config/data/hivtb => classify/config/data}/__init__.py (100%)
rename src/mednet/{libs/classification/config/data/indian => classify/config/data/hivtb}/__init__.py (100%)
rename src/mednet/{libs/classification => classify}/config/data/hivtb/datamodule.py (86%)
rename src/mednet/{libs/classification => classify}/config/data/hivtb/fold-0.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/hivtb/fold-1.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/hivtb/fold-2.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/hivtb/fold-3.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/hivtb/fold-4.json (100%)
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rename src/mednet/{libs/classification => classify}/config/data/hivtb/fold-7.json (100%)
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rename src/mednet/{libs/classification => classify}/config/data/hivtb/fold-9.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/hivtb/fold_0.py (60%)
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rename src/mednet/{libs/classification => classify}/config/data/hivtb/fold_8.py (60%)
rename src/mednet/{libs/classification => classify}/config/data/hivtb/fold_9.py (60%)
rename src/mednet/{libs/classification/config/data/montgomery => classify/config/data/indian}/__init__.py (100%)
rename src/mednet/{libs/classification => classify}/config/data/indian/datamodule.py (91%)
rename src/mednet/{libs/classification => classify}/config/data/indian/default.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/indian/default.py (60%)
rename src/mednet/{libs/classification => classify}/config/data/indian/fold-0.json (100%)
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rename src/mednet/{libs/classification => classify}/config/data/indian/fold-9.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/indian/fold_0.py (61%)
rename src/mednet/{libs/classification => classify}/config/data/indian/fold_1.py (61%)
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rename src/mednet/{libs/classification => classify}/config/data/indian/fold_6.py (61%)
rename src/mednet/{libs/classification => classify}/config/data/indian/fold_7.py (61%)
rename src/mednet/{libs/classification => classify}/config/data/indian/fold_8.py (61%)
rename src/mednet/{libs/classification => classify}/config/data/indian/fold_9.py (61%)
rename src/mednet/{libs/classification/config/data/montgomery_shenzhen => classify/config/data/montgomery}/__init__.py (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/datamodule.py (87%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/default.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/default.py (61%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold-0.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold-1.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold-2.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold-3.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold-4.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold-5.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold-6.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold-7.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold-8.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold-9.json (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold_0.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold_1.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold_2.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold_3.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold_4.py (59%)
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rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold_6.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold_7.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold_8.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery/fold_9.py (59%)
rename src/mednet/{libs/classification/config/data/montgomery_shenzhen_indian => classify/config/data/montgomery_shenzhen}/__init__.py (100%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/datamodule.py (89%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/default.py (61%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/fold_0.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/fold_1.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/fold_2.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/fold_3.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/fold_4.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/fold_5.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/fold_6.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/fold_7.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/fold_8.py (59%)
rename src/mednet/{libs/classification => classify}/config/data/montgomery_shenzhen/fold_9.py (59%)
rename src/mednet/{libs/classification/config/data/montgomery_shenzhen_indian_padchest => classify/config/data/montgomery_shenzhen_indian}/__init__.py (100%)
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rename src/mednet/{libs/segmentation => segment}/config/data/rimoner3/optic-cup-avg.json (100%)
rename src/mednet/{libs/segmentation => segment}/config/data/rimoner3/optic-cup-exp1.json (100%)
rename src/mednet/{libs/segmentation => segment}/config/data/rimoner3/optic-cup-exp2.json (100%)
rename src/mednet/{libs/segmentation => segment}/config/data/rimoner3/optic-disc-avg.json (100%)
rename src/mednet/{libs/segmentation => segment}/config/data/rimoner3/optic-disc-exp1.json (100%)
rename src/mednet/{libs/segmentation => segment}/config/data/rimoner3/optic-disc-exp2.json (100%)
rename src/mednet/{libs/segmentation/config/data/montgomery => segment/config/data/shenzhen}/__init__.py (100%)
rename src/mednet/{libs/segmentation => segment}/config/data/shenzhen/datamodule.py (88%)
rename src/mednet/{libs/segmentation => segment}/config/data/shenzhen/default.json (100%)
rename src/mednet/{libs/segmentation => segment}/config/data/shenzhen/default.py (77%)
rename src/mednet/{libs/segmentation/config/data/refuge => segment/config/data/stare}/__init__.py (100%)
rename src/mednet/{libs/segmentation => segment}/config/data/stare/ah.json (100%)
rename src/mednet/{libs/segmentation => segment}/config/data/stare/ah.py (81%)
rename src/mednet/{libs/segmentation => segment}/config/data/stare/datamodule.py (89%)
rename src/mednet/{libs/segmentation => segment}/config/data/stare/masks/stare-images/im0001.png (100%)
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rename src/mednet/{libs/segmentation => segment}/config/data/stare/vk.py (81%)
rename src/mednet/{libs/segmentation/config/data/rimoner3 => segment/config/models}/__init__.py (100%)
rename src/mednet/{libs/segmentation => segment}/config/models/driu.py (65%)
rename src/mednet/{libs/segmentation => segment}/config/models/driu_bn.py (65%)
rename src/mednet/{libs/segmentation => segment}/config/models/driu_od.py (64%)
rename src/mednet/{libs/segmentation => segment}/config/models/driu_pix.py (64%)
rename src/mednet/{libs/segmentation => segment}/config/models/hed.py (56%)
rename src/mednet/{libs/segmentation => segment}/config/models/lwnet.py (71%)
rename src/mednet/{libs/segmentation => segment}/config/models/m2unet.py (73%)
rename src/mednet/{libs/segmentation => segment}/config/models/unet.py (69%)
rename src/mednet/{libs/segmentation/config/data/shenzhen => segment/data}/__init__.py (100%)
rename src/mednet/{libs/segmentation => segment}/data/typing.py (75%)
rename src/mednet/{libs/segmentation/config/data/stare => segment/engine}/__init__.py (100%)
rename src/mednet/{libs/segmentation => segment}/engine/dumper.py (100%)
rename src/mednet/{libs/segmentation => segment}/engine/evaluator.py (97%)
rename src/mednet/{libs/segmentation => segment}/engine/predictor.py (99%)
rename src/mednet/{libs/segmentation => segment}/engine/viewer.py (100%)
rename src/mednet/{libs/segmentation/config => segment}/models/__init__.py (100%)
rename src/mednet/{libs/segmentation/data => segment/models/backbones}/__init__.py (100%)
rename src/mednet/{libs/segmentation => segment}/models/backbones/mobilenetv2.py (100%)
rename src/mednet/{libs/segmentation => segment}/models/backbones/vgg.py (100%)
rename src/mednet/{libs/segmentation => segment}/models/driu.py (98%)
rename src/mednet/{libs/segmentation => segment}/models/driu_bn.py (98%)
rename src/mednet/{libs/segmentation => segment}/models/driu_od.py (98%)
rename src/mednet/{libs/segmentation => segment}/models/driu_pix.py (98%)
rename src/mednet/{libs/segmentation => segment}/models/hed.py (98%)
rename src/mednet/{libs/segmentation => segment}/models/losses.py (100%)
rename src/mednet/{libs/segmentation => segment}/models/lwnet.py (98%)
rename src/mednet/{libs/segmentation => segment}/models/m2unet.py (98%)
rename src/mednet/{libs/segmentation => segment}/models/make_layers.py (100%)
rename src/mednet/{libs/segmentation => segment}/models/normalizer.py (100%)
rename src/mednet/{libs/segmentation => segment}/models/segmentation_model.py (95%)
rename src/mednet/{libs/segmentation => segment}/models/unet.py (98%)
rename src/mednet/{libs/segmentation/engine => segment/scripts}/__init__.py (100%)
create mode 100644 src/mednet/segment/scripts/cli.py
rename src/mednet/{libs/segmentation => segment}/scripts/dump_annotations.py (79%)
rename src/mednet/{libs/segmentation => segment}/scripts/evaluate.py (95%)
rename src/mednet/{libs/segmentation => segment}/scripts/view.py (92%)
rename src/mednet/{libs/segmentation/models => utils}/__init__.py (100%)
rename src/mednet/{libs/common => }/utils/checkpointer.py (100%)
rename src/mednet/{libs/common => }/utils/rc.py (100%)
rename src/mednet/{libs/common => }/utils/resources.py (99%)
rename src/mednet/{libs/common => }/utils/summary.py (100%)
rename src/mednet/{libs/common => }/utils/tensorboard.py (100%)
delete mode 100644 tests/classification/__init__.py
rename {src/mednet/libs/segmentation/models/backbones => tests/classify}/__init__.py (100%)
rename tests/{classification => classify}/data/histograms/models/histograms_alexnet_montgomery_default.json (100%)
rename tests/{classification => classify}/data/histograms/models/histograms_densenet-121_montgomery_default.json (100%)
rename tests/{classification => classify}/data/histograms/models/histograms_pasa_montgomery_default.json (100%)
rename tests/{classification => classify}/data/histograms/raw_data/histograms_hivtb_fold_0.json (100%)
rename tests/{classification => classify}/data/histograms/raw_data/histograms_indian_default.json (100%)
rename tests/{classification => classify}/data/histograms/raw_data/histograms_montgomery_default.json (100%)
rename tests/{classification => classify}/data/histograms/raw_data/histograms_montgomery_preprocessed_default.json (100%)
rename tests/{classification => classify}/data/histograms/raw_data/histograms_nih_cxr14_default.json (100%)
rename tests/{classification => classify}/data/histograms/raw_data/histograms_padchest_idiap.json (100%)
rename tests/{classification => classify}/data/histograms/raw_data/histograms_shenzhen_default.json (100%)
rename tests/{classification => classify}/data/histograms/raw_data/histograms_tbpoc_fold_0.json (100%)
rename tests/{classification => classify}/data/histograms/raw_data/histograms_tbx11k_v1_fold_0.json (100%)
rename tests/{classification => classify}/data/histograms/raw_data/histograms_tbx11k_v2_fold_0.json (100%)
rename tests/{classification => classify}/data/test_predictions.csv (100%)
rename tests/{classification => classify}/data/test_vis_metrics.csv (100%)
rename tests/{classification => classify}/test_cli.py (80%)
rename tests/{classification => classify}/test_evaluator.py (85%)
rename tests/{classification => classify}/test_hivtb.py (90%)
rename tests/{classification => classify}/test_indian.py (91%)
rename tests/{classification => classify}/test_montgomery.py (91%)
rename tests/{classification => classify}/test_montgomery_shenzhen.py (83%)
rename tests/{classification => classify}/test_montgomery_shenzhen_indian.py (82%)
rename tests/{classification => classify}/test_montgomery_shenzhen_indian_padchest.py (81%)
rename tests/{classification => classify}/test_montgomery_shenzhen_indian_tbx11k.py (85%)
rename tests/{classification => classify}/test_nih_cxr14.py (89%)
rename tests/{classification => classify}/test_nih_cxr14_padchest.py (83%)
rename tests/{classification => classify}/test_padchest.py (90%)
rename tests/{classification => classify}/test_saliencymap_interpretability.py (97%)
rename tests/{classification => classify}/test_shenzhen.py (90%)
rename tests/{classification => classify}/test_summary.py (77%)
rename tests/{classification => classify}/test_tbpoc.py (87%)
rename tests/{classification => classify}/test_tbx11k.py (96%)
rename tests/{classification => classify}/test_visceral.py (83%)
rename {src/mednet/libs/segmentation/scripts => tests/segment}/__init__.py (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_cxr8_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_drhagis_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_drionsdb_expert1.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_drishtigs1_optic_cup_all.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_drive_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_hrf_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_iostar_vessel.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_jsrt_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_montgomery_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_refuge_cup.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_rimoner3_cup_exp1.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_shenzhen_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/models/histograms_lwnet_stare_ah.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_chasedb1_first_annotator.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_cxr8_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_drhagis_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_drionsdb_expert1.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_drishtigs1_optic_cup_all.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_drive_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_hrf_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_iostar_vessel.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_jsrt_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_montgomery_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_refuge_cup.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_rimoner3_cup_exp1.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_shenzhen_default.json (100%)
rename tests/{segmentation => segment}/data/histograms/raw_data/histograms_stare_ah.json (100%)
rename tests/{segmentation => segment}/test_chasedb1.py (78%)
rename tests/{segmentation => segment}/test_cli.py (82%)
rename tests/{segmentation => segment}/test_cxr8.py (88%)
rename tests/{segmentation => segment}/test_drhagis.py (88%)
rename tests/{segmentation => segment}/test_drionsdb.py (79%)
rename tests/{segmentation => segment}/test_drishtigs1.py (89%)
rename tests/{segmentation => segment}/test_drive.py (88%)
rename tests/{segmentation => segment}/test_hrf.py (80%)
rename tests/{segmentation => segment}/test_iostar.py (88%)
rename tests/{segmentation => segment}/test_jsrt.py (77%)
rename tests/{segmentation => segment}/test_measures.py (90%)
rename tests/{segmentation => segment}/test_montgomery.py (88%)
rename tests/{segmentation => segment}/test_refuge.py (84%)
rename tests/{segmentation => segment}/test_rimoner3.py (89%)
rename tests/{segmentation => segment}/test_shenzhen.py (88%)
rename tests/{segmentation => segment}/test_stare.py (82%)
delete mode 100644 tests/segmentation/__init__.py
diff --git a/doc/api.rst b/doc/api.rst
index 6c5bf8ae..04aca648 100644
--- a/doc/api.rst
+++ b/doc/api.rst
@@ -2,22 +2,22 @@
..
.. SPDX-License-Identifier: GPL-3.0-or-later
-.. _mednet.libs.classification.api:
+.. _mednet.classify.api:
============
Python API
============
-This section includes information for using the Python API of
-``mednet``.
+This section includes information for using the Python API of ``mednet``.
-Common library
---------------
+Core Components
+---------------
-This common library contains methods and scripts that can be reused by more specialized libraries.
+This part of mednet contains methods and scripts that can be reused by more
+specialized libraries.
-.. _mednet.libs.common.api.data:
+.. _mednet.api.data:
Data Methods
^^^^^^^^^^^^
@@ -27,46 +27,60 @@ Auxiliary classes and methods to define raw dataset iterators.
.. autosummary::
:toctree: api/data
- mednet.libs.common.data.augmentations
- mednet.libs.common.data.datamodule
- mednet.libs.common.data.image_utils
- mednet.libs.common.data.split
- mednet.libs.common.data.typing
+ mednet.data.augmentations
+ mednet.data.datamodule
+ mednet.data.image_utils
+ mednet.data.split
+ mednet.data.typing
+ mednet.classify.data.typing
+ mednet.segment.data.typing
-.. _mednet.libs.common.api.engines:
+.. _mednet.api.engines:
Command engines
^^^^^^^^^^^^^^^
-Functions to actuate on the data.
+Functions that operate on data.
.. autosummary::
- :toctree: api/engine
+ :toctree: api/engines
- mednet.libs.common.engine.callbacks
- mednet.libs.common.engine.device
- mednet.libs.common.engine.loggers
- mednet.libs.common.engine.trainer
+ mednet.engine.callbacks
+ mednet.engine.device
+ mednet.engine.loggers
+ mednet.engine.trainer
+ mednet.engine.uploader
+ mednet.classify.engine.evaluator
+ mednet.classify.engine.predictor
+ mednet.classify.engine.saliency.completeness
+ mednet.classify.engine.saliency.evaluator
+ mednet.classify.engine.saliency.generator
+ mednet.classify.engine.saliency.interpretability
+ mednet.classify.engine.saliency.viewer
+ mednet.segment.engine.dumper
+ mednet.segment.engine.evaluator
+ mednet.segment.engine.predictor
+ mednet.segment.engine.viewer
-.. _mednet.libs.common.api.models:
+.. _mednet.api.models.support:
-Models
-^^^^^^
+Modelling Suppoort
+^^^^^^^^^^^^^^^^^^
-Common model utilities.
+Model definitions and utilities.
.. autosummary::
- :toctree: api/models
+ :toctree: api/models/support
- mednet.libs.common.models.loss_weights
- mednet.libs.common.models.model
- mednet.libs.common.models.transforms
- mednet.libs.common.models.typing
+ mednet.models.loss_weights
+ mednet.models.transforms
+ mednet.models.typing
+ mednet.models.model
-.. _mednet.libs.common.api.utils:
+.. _mednet.api.utils:
Utils
^^^^^
@@ -76,151 +90,97 @@ Reusable auxiliary functions.
.. autosummary::
:toctree: api/utils
- mednet.libs.common.utils.checkpointer
- mednet.libs.common.utils.gitlab
- mednet.libs.common.utils.rc
- mednet.libs.common.utils.resources
- mednet.libs.common.utils.summary
- mednet.libs.common.utils.tensorboard
+ mednet.utils.checkpointer
+ mednet.utils.rc
+ mednet.utils.resources
+ mednet.utils.summary
+ mednet.utils.tensorboard
-Classification library
-----------------------
+.. _mednet.api.classify.models:
-Library for training models on classification tasks
+Classification models
+---------------------
+Library for training models on classification tasks.
-.. _mednet.libs.classification.api.data:
-Data
-^^^^
+.. _mednet.api.classify.models.support:
-Classification-specific data methods
+Modelling Support
+^^^^^^^^^^^^^^^^^
-.. autosummary::
- :toctree: api/data
-
- mednet.libs.classification.data.typing
-
-
-.. _mednet.libs.classification.api.engines:
-
-Command engines
-^^^^^^^^^^^^^^^
-
-Functions to actuate on the data.
+Classification model definitions and utilities.
.. autosummary::
- :toctree: api/engine
+ :toctree: api/classify/models/support
- mednet.libs.classification.engine.evaluator
- mednet.libs.classification.engine.predictor
+ mednet.classify.models.classification_model
+ mednet.classify.models.loss_weights
+ mednet.classify.models.normalizer
+ mednet.classify.models.typing
-.. _mednet.libs.classification.api.models:
+.. _mednet.api.classify.models.available:
-Models
-^^^^^^
+Available Models
+^^^^^^^^^^^^^^^^
-CNN and other models implemented.
+Available classification models.
.. autosummary::
- :toctree: api/models
-
- mednet.libs.classification.models.pasa
- mednet.libs.classification.models.alexnet
- mednet.libs.classification.models.classification_model
- mednet.libs.classification.models.densenet
- mednet.libs.classification.models.loss_weights
- mednet.libs.classification.models.logistic_regression
- mednet.libs.classification.models.mlp
- mednet.libs.classification.models.normalizer
- mednet.libs.classification.models.typing
-
-
-.. _mednet.libs.classification.api.saliency:
-
-Saliency Map Generation and Analysis
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Engines to generate and analyze saliency mapping techniques.
-
-.. autosummary::
- :toctree: api/saliency
-
- mednet.libs.classification.engine.saliency.completeness
- mednet.libs.classification.engine.saliency.evaluator
- mednet.libs.classification.engine.saliency.generator
- mednet.libs.classification.engine.saliency.interpretability
- mednet.libs.classification.engine.saliency.viewer
+ :toctree: api/classify/models/available
+ mednet.classify.models.alexnet
+ mednet.classify.models.densenet
+ mednet.classify.models.pasa
+ mednet.classify.models.logistic_regression
+ mednet.classify.models.mlp
-.. _mednet.libs.classification.api.utils:
-Utils
-^^^^^
-
-Classification-specific utilities.
-
-.. autosummary::
- :toctree: api/utils
-
- mednet.libs.common.utils.rc
+.. _mednet.api.segment.models:
Segmentation library
--------------------
-Library for training models on segmentation tasks
-
-
-.. _mednet.libs.segmentation.api.data:
+Library for training models on semantic segmentation tasks.
-Data
-^^^^
-Segmentation-specific data methods
+.. _mednet.api.segment.models.support:
-.. autosummary::
- :toctree: api/data
-
- mednet.libs.segmentation.data.typing
-
-
-.. _mednet.libs.segmentation.api.engines:
-
-Command engines
-^^^^^^^^^^^^^^^
+Modelling Support
+^^^^^^^^^^^^^^^^^
-Functions to actuate on the data.
+Semantic segmentation model definitions and utilities.
.. autosummary::
- :toctree: api/engine
+ :toctree: api/segment/models/support
- mednet.libs.segmentation.engine.evaluator
+ mednet.segment.models.segmentation_model
+ mednet.segment.models.normalizer
+ mednet.segment.models.make_layers
+ mednet.segment.models.losses
-.. _mednet.libs.segmentation.api.models:
+.. _mednet.api.segment.models.available:
-Models
-^^^^^^
+Available Models
+^^^^^^^^^^^^^^^^
-CNN and other models implemented.
+Available semantic segmentation models.
.. autosummary::
- :toctree: api/models
-
- mednet.libs.segmentation.models.driu_bn
- mednet.libs.segmentation.models.driu_od
- mednet.libs.segmentation.models.driu_pix
- mednet.libs.segmentation.models.driu
- mednet.libs.segmentation.models.hed
- mednet.libs.segmentation.models.losses
- mednet.libs.segmentation.models.lwnet
- mednet.libs.segmentation.models.m2unet
- mednet.libs.segmentation.models.normalizer
- mednet.libs.segmentation.models.segmentation_model
- mednet.libs.segmentation.models.unet
+ :toctree: api/segment/models/available
+
+ mednet.segment.models.driu_bn
+ mednet.segment.models.driu_od
+ mednet.segment.models.driu_pix
+ mednet.segment.models.driu
+ mednet.segment.models.hed
+ mednet.segment.models.lwnet
+ mednet.segment.models.m2unet
+ mednet.segment.models.unet
.. include:: links.rst
diff --git a/doc/cli.rst b/doc/cli.rst
index fd01e8a7..0d9ebcec 100644
--- a/doc/cli.rst
+++ b/doc/cli.rst
@@ -2,7 +2,7 @@
..
.. SPDX-License-Identifier: GPL-3.0-or-later
-.. _mednet.libs.common.cli:
+.. _mednet.cli:
========================
Command-line Interface
diff --git a/doc/config.rst b/doc/config.rst
index 98865ee6..01a2d3e4 100644
--- a/doc/config.rst
+++ b/doc/config.rst
@@ -7,17 +7,19 @@ Preset Configurations
=====================
-.. _mednet.libs.classification.config:
+.. _mednet.config:
-------------------------------------
-Classification Preset Configurations
-------------------------------------
+.. _mednet.config.classify:
+
+-----------------------------
+Classification Configurations
+-----------------------------
This module contains preset configurations for baseline CNN architectures and
-DataModules in a classification task.
+DataModules for classification tasks.
-.. _mednet.libs.classification.config.models:
+.. _mednet.config.classify.models:
Pre-configured Models
^^^^^^^^^^^^^^^^^^^^^
@@ -25,48 +27,49 @@ Pre-configured Models
Pre-configured models you can readily use.
.. autosummary::
- :toctree: api/config.models
+ :toctree: api/config-classify-models
:template: config.rst
- mednet.libs.classification.config.models.alexnet
- mednet.libs.classification.config.models.alexnet_pretrained
- mednet.libs.classification.config.models.densenet
- mednet.libs.classification.config.models.densenet_pretrained
- mednet.libs.classification.config.models.densenet_rs
- mednet.libs.classification.config.models.logistic_regression
- mednet.libs.classification.config.models.mlp
- mednet.libs.classification.config.models.pasa
+ mednet.classify.config.models.alexnet
+ mednet.classify.config.models.alexnet_pretrained
+ mednet.classify.config.models.densenet
+ mednet.classify.config.models.densenet_pretrained
+ mednet.classify.config.models.densenet_rs
+ mednet.classify.config.models.logistic_regression
+ mednet.classify.config.models.mlp
+ mednet.classify.config.models.pasa
-.. _mednet.libs.classification.config.datamodules:
+.. _mednet.config.classify.datamodules:
-DataModule support
+DataModule Support
^^^^^^^^^^^^^^^^^^
Base DataModules and raw data loaders for the various databases currently
-supported in this package, for your reference. Each pre-configured DataModule
-can receive the name of one or more splits as argument to build a fully
-functional DataModule that can be used in training, prediction or testing.
+supported in this package, for classification tasks. Each pre-configured
+DataModule can receive the name of one or more splits as argument to build a
+fully functional DataModule that can be used in training, prediction or
+testing.
.. autosummary::
- :toctree: api/config.datamodules
+ :toctree: api/config-classify-datamodules
- mednet.libs.classification.config.data.hivtb.datamodule
- mednet.libs.classification.config.data.indian.datamodule
- mednet.libs.classification.config.data.montgomery.datamodule
- mednet.libs.classification.config.data.montgomery_shenzhen.datamodule
- mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule
- mednet.libs.classification.config.data.montgomery_shenzhen_indian_padchest.datamodule
- mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule
- mednet.libs.classification.config.data.nih_cxr14.datamodule
- mednet.libs.classification.config.data.nih_cxr14_padchest.datamodule
- mednet.libs.classification.config.data.padchest.datamodule
- mednet.libs.classification.config.data.shenzhen.datamodule
- mednet.libs.classification.config.data.tbpoc.datamodule
- mednet.libs.classification.config.data.tbx11k.datamodule
+ mednet.classify.config.data.hivtb.datamodule
+ mednet.classify.config.data.indian.datamodule
+ mednet.classify.config.data.montgomery.datamodule
+ mednet.classify.config.data.montgomery_shenzhen.datamodule
+ mednet.classify.config.data.montgomery_shenzhen_indian.datamodule
+ mednet.classify.config.data.montgomery_shenzhen_indian_padchest.datamodule
+ mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule
+ mednet.classify.config.data.nih_cxr14.datamodule
+ mednet.classify.config.data.nih_cxr14_padchest.datamodule
+ mednet.classify.config.data.padchest.datamodule
+ mednet.classify.config.data.shenzhen.datamodule
+ mednet.classify.config.data.tbpoc.datamodule
+ mednet.classify.config.data.tbx11k.datamodule
-.. _mednet.libs.classification.config.datamodule-instances:
+.. _mednet.config.classify.datamodule-instances:
Pre-configured DataModules
^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -74,29 +77,29 @@ Pre-configured DataModules
DataModules provide access to preset pytorch dataloaders for training,
validating, testing and running prediction tasks. Each of the pre-configured
DataModule is based on one (or more) of the :ref:`supported base DataModules
-<mednet.libs.classification.config.datamodules>`.
+<mednet.config.classify.datamodules>`.
.. autosummary::
- :toctree: api/config.datamodule-instances
+ :toctree: api/config-classify-datamodule-instances
:template: config.rst
- mednet.libs.classification.config.data.indian.default
- mednet.libs.classification.config.data.montgomery.default
- mednet.libs.classification.config.data.montgomery_shenzhen.default
- mednet.libs.classification.config.data.montgomery_shenzhen_indian.default
- mednet.libs.classification.config.data.montgomery_shenzhen_indian_padchest.default
- mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_healthy_vs_atb
- mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_others_vs_atb
- mednet.libs.classification.config.data.nih_cxr14.default
- mednet.libs.classification.config.data.nih_cxr14_padchest.idiap
- mednet.libs.classification.config.data.padchest.idiap
- mednet.libs.classification.config.data.shenzhen.default
- mednet.libs.classification.config.data.tbx11k.v1_healthy_vs_atb
- mednet.libs.classification.config.data.tbx11k.v2_others_vs_atb
- mednet.libs.classification.config.data.tbx11k.v2_others_vs_atb
+ mednet.classify.config.data.indian.default
+ mednet.classify.config.data.montgomery.default
+ mednet.classify.config.data.montgomery_shenzhen.default
+ mednet.classify.config.data.montgomery_shenzhen_indian.default
+ mednet.classify.config.data.montgomery_shenzhen_indian_padchest.default
+ mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_healthy_vs_atb
+ mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_others_vs_atb
+ mednet.classify.config.data.nih_cxr14.default
+ mednet.classify.config.data.nih_cxr14_padchest.idiap
+ mednet.classify.config.data.padchest.idiap
+ mednet.classify.config.data.shenzhen.default
+ mednet.classify.config.data.tbx11k.v1_healthy_vs_atb
+ mednet.classify.config.data.tbx11k.v2_others_vs_atb
+ mednet.classify.config.data.tbx11k.v2_others_vs_atb
-.. _mednet.libs.classification.config.datamodule-instances.folds:
+.. _mednet.classify.config.datamodule-instances.folds:
Cross-validation DataModules
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -108,33 +111,33 @@ DataModules. Nine other folds are available for every configuration (from 1 to
.. autosummary::
- :toctree: api/config.datamodule-folds
+ :toctree: api/config-classify-datamodule-folds
:template: config.rst
- mednet.libs.classification.config.data.hivtb.fold_0
- mednet.libs.classification.config.data.indian.fold_0
- mednet.libs.classification.config.data.montgomery.fold_0
- mednet.libs.classification.config.data.montgomery_shenzhen.fold_0
- mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_0
- mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_0
- mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_0
- mednet.libs.classification.config.data.shenzhen.fold_0
- mednet.libs.classification.config.data.tbpoc.fold_0
- mednet.libs.classification.config.data.tbx11k.v1_fold_0
- mednet.libs.classification.config.data.tbx11k.v2_fold_0
+ mednet.classify.config.data.hivtb.fold_0
+ mednet.classify.config.data.indian.fold_0
+ mednet.classify.config.data.montgomery.fold_0
+ mednet.classify.config.data.montgomery_shenzhen.fold_0
+ mednet.classify.config.data.montgomery_shenzhen_indian.fold_0
+ mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_0
+ mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_0
+ mednet.classify.config.data.shenzhen.fold_0
+ mednet.classify.config.data.tbpoc.fold_0
+ mednet.classify.config.data.tbx11k.v1_fold_0
+ mednet.classify.config.data.tbx11k.v2_fold_0
-.. _mednet.libs.segmentation.config:
+.. _mednet.config.segment:
------------------------------------
-Classification Preset Configurations
+Semantic Segmentation Configurations
------------------------------------
-This module contains preset configurations for baseline CNN architectures and
-DataModules in a segmentation task.
+This module contains preset configurations for baseline semantic segmentation
+architectures and DataModules.
-.. _mednet.libs.segmentation.config.models:
+.. _mednet.config.segment.models:
Pre-configured Models
^^^^^^^^^^^^^^^^^^^^^
@@ -142,20 +145,20 @@ Pre-configured Models
Pre-configured models you can readily use.
.. autosummary::
- :toctree: api/config.models
+ :toctree: api/config-segment-models
:template: config.rst
- mednet.libs.segmentation.config.models.driu_bn
- mednet.libs.segmentation.config.models.driu_od
- mednet.libs.segmentation.config.models.driu_pix
- mednet.libs.segmentation.config.models.driu
- mednet.libs.segmentation.config.models.hed
- mednet.libs.segmentation.config.models.lwnet
- mednet.libs.segmentation.config.models.m2unet
- mednet.libs.segmentation.config.models.unet
+ mednet.segment.config.models.driu_bn
+ mednet.segment.config.models.driu_od
+ mednet.segment.config.models.driu_pix
+ mednet.segment.config.models.driu
+ mednet.segment.config.models.hed
+ mednet.segment.config.models.lwnet
+ mednet.segment.config.models.m2unet
+ mednet.segment.config.models.unet
-.. _mednet.libs.segmentation.config.datamodules:
+.. _mednet.config.segment.datamodules:
DataModule support
^^^^^^^^^^^^^^^^^^
@@ -166,25 +169,25 @@ can receive the name of one or more splits as argument to build a fully
functional DataModule that can be used in training, prediction or testing.
.. autosummary::
- :toctree: api/config.datamodules
-
- mednet.libs.segmentation.config.data.chasedb1.datamodule
- mednet.libs.segmentation.config.data.cxr8.datamodule
- mednet.libs.segmentation.config.data.drhagis.datamodule
- mednet.libs.segmentation.config.data.drionsdb.datamodule
- mednet.libs.segmentation.config.data.drishtigs1.datamodule
- mednet.libs.segmentation.config.data.drive.datamodule
- mednet.libs.segmentation.config.data.hrf.datamodule
- mednet.libs.segmentation.config.data.iostar.datamodule
- mednet.libs.segmentation.config.data.jsrt.datamodule
- mednet.libs.segmentation.config.data.montgomery.datamodule
- mednet.libs.segmentation.config.data.refuge.datamodule
- mednet.libs.segmentation.config.data.rimoner3.datamodule
- mednet.libs.segmentation.config.data.shenzhen.datamodule
- mednet.libs.segmentation.config.data.stare.datamodule
-
-
-.. _mednet.libs.segmentation.config.datamodule-instances:
+ :toctree: api/config-segment-datamodules
+
+ mednet.segment.config.data.chasedb1.datamodule
+ mednet.segment.config.data.cxr8.datamodule
+ mednet.segment.config.data.drhagis.datamodule
+ mednet.segment.config.data.drionsdb.datamodule
+ mednet.segment.config.data.drishtigs1.datamodule
+ mednet.segment.config.data.drive.datamodule
+ mednet.segment.config.data.hrf.datamodule
+ mednet.segment.config.data.iostar.datamodule
+ mednet.segment.config.data.jsrt.datamodule
+ mednet.segment.config.data.montgomery.datamodule
+ mednet.segment.config.data.refuge.datamodule
+ mednet.segment.config.data.rimoner3.datamodule
+ mednet.segment.config.data.shenzhen.datamodule
+ mednet.segment.config.data.stare.datamodule
+
+
+.. _mednet.config.segment.datamodule-instances:
Pre-configured DataModules
^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -192,38 +195,38 @@ Pre-configured DataModules
DataModules provide access to preset pytorch dataloaders for training,
validating, testing and running prediction tasks. Each of the pre-configured
DataModule is based on one (or more) of the :ref:`supported base DataModules
-<mednet.libs.segmentation.config.datamodules>`.
+<mednet.config.segment.datamodules>`.
.. autosummary::
- :toctree: api/config.datamodule-instances
+ :toctree: api/config-segment-datamodule-instances
:template: config.rst
- mednet.libs.segmentation.config.data.chasedb1.first_annotator
- mednet.libs.segmentation.config.data.chasedb1.second_annotator
- mednet.libs.segmentation.config.data.cxr8.default
- mednet.libs.segmentation.config.data.drhagis.default
- mednet.libs.segmentation.config.data.drionsdb.expert1
- mednet.libs.segmentation.config.data.drionsdb.expert2
- mednet.libs.segmentation.config.data.drishtigs1.optic_cup_all
- mednet.libs.segmentation.config.data.drishtigs1.optic_cup_any
- mednet.libs.segmentation.config.data.drishtigs1.optic_disc_all
- mednet.libs.segmentation.config.data.drishtigs1.optic_disc_any
- mednet.libs.segmentation.config.data.drive.default
- mednet.libs.segmentation.config.data.drive.drive_2nd
- mednet.libs.segmentation.config.data.hrf.default
- mednet.libs.segmentation.config.data.iostar.optic_disc
- mednet.libs.segmentation.config.data.iostar.vessel
- mednet.libs.segmentation.config.data.jsrt.default
- mednet.libs.segmentation.config.data.montgomery.default
- mednet.libs.segmentation.config.data.refuge.disc
- mednet.libs.segmentation.config.data.refuge.cup
- mednet.libs.segmentation.config.data.rimoner3.cup_exp1
- mednet.libs.segmentation.config.data.rimoner3.cup_exp2
- mednet.libs.segmentation.config.data.rimoner3.disc_exp1
- mednet.libs.segmentation.config.data.rimoner3.disc_exp2
- mednet.libs.segmentation.config.data.shenzhen.default
- mednet.libs.segmentation.config.data.stare.ah
- mednet.libs.segmentation.config.data.stare.vk
+ mednet.segment.config.data.chasedb1.first_annotator
+ mednet.segment.config.data.chasedb1.second_annotator
+ mednet.segment.config.data.cxr8.default
+ mednet.segment.config.data.drhagis.default
+ mednet.segment.config.data.drionsdb.expert1
+ mednet.segment.config.data.drionsdb.expert2
+ mednet.segment.config.data.drishtigs1.optic_cup_all
+ mednet.segment.config.data.drishtigs1.optic_cup_any
+ mednet.segment.config.data.drishtigs1.optic_disc_all
+ mednet.segment.config.data.drishtigs1.optic_disc_any
+ mednet.segment.config.data.drive.default
+ mednet.segment.config.data.drive.drive_2nd
+ mednet.segment.config.data.hrf.default
+ mednet.segment.config.data.iostar.optic_disc
+ mednet.segment.config.data.iostar.vessel
+ mednet.segment.config.data.jsrt.default
+ mednet.segment.config.data.montgomery.default
+ mednet.segment.config.data.refuge.disc
+ mednet.segment.config.data.refuge.cup
+ mednet.segment.config.data.rimoner3.cup_exp1
+ mednet.segment.config.data.rimoner3.cup_exp2
+ mednet.segment.config.data.rimoner3.disc_exp1
+ mednet.segment.config.data.rimoner3.disc_exp2
+ mednet.segment.config.data.shenzhen.default
+ mednet.segment.config.data.stare.ah
+ mednet.segment.config.data.stare.vk
------------------
@@ -232,14 +235,18 @@ Data Augmentations
Sequences of data augmentations you can readily use.
-.. _mednet.libs.common.config.augmentations:
+.. _mednet.config.augmentations:
.. autosummary::
- :toctree: api/config.augmentations
+ :toctree: api/config-augmentations
:template: config.rst
- mednet.libs.common.config.augmentations.elastic
- mednet.libs.common.config.augmentations.affine
+ mednet.config.augmentations.affine
+ mednet.config.augmentations.elastic
+ mednet.config.augmentations.hflip
+ mednet.config.augmentations.hflip_affine
+ mednet.config.augmentations.hflip_jitter_affine
+ mednet.config.augmentations.jitter
.. include:: links.rst
diff --git a/doc/contribute.rst b/doc/contribute.rst
index 849a9e48..0c25cfa8 100644
--- a/doc/contribute.rst
+++ b/doc/contribute.rst
@@ -2,7 +2,7 @@
..
.. SPDX-License-Identifier: GPL-3.0-or-later
-.. _mednet.libs.classification.contribute:
+.. _mednet.contribute:
===================================
Getting Involved and Contributing
diff --git a/doc/data-model.rst b/doc/data-model.rst
index 6448c324..9fdbd08a 100644
--- a/doc/data-model.rst
+++ b/doc/data-model.rst
@@ -2,7 +2,7 @@
..
.. SPDX-License-Identifier: GPL-3.0-or-later
-.. _mednet.libs.classification.datamodel:
+.. _mednet.datamodel:
============
Data model
@@ -39,8 +39,8 @@ Sample
------
The in-memory representation of the raw database samples. In this package, it
-is specified as a two-tuple with a tensor, and metadata (typically label, name,
-etc.).
+is specified as a two-tuple with a tensor (or a dictionary with multiple
+tensors), and metadata (typically label, name, etc.).
RawDataLoader
diff --git a/doc/install.rst b/doc/install.rst
index 61bfda53..167ff202 100644
--- a/doc/install.rst
+++ b/doc/install.rst
@@ -2,7 +2,7 @@
..
.. SPDX-License-Identifier: GPL-3.0-or-later
-.. _mednet.libs.classification.install:
+.. _mednet.install:
==============
Installation
@@ -78,7 +78,7 @@ installation paths.
configuration tips on the *Development* tab above.
-.. _mednet.libs.classification.setup:
+.. _mednet.setup:
Setup
-----
@@ -86,8 +86,7 @@ Setup
A configuration file may be useful to setup global options that should be often
reused. The location of the configuration file depends on the value of the
environment variable ``$XDG_CONFIG_HOME``, but defaults to
-``~/.config/mednet.libs.classification.toml``. You may edit this file using your preferred
-editor.
+``~/.config/mednet.toml``. You may edit this file using your preferred editor.
Here is an example configuration file that may be useful as a starting point:
@@ -100,6 +99,30 @@ Here is an example configuration file that may be useful as a starting point:
nih_cxr14_re = "/Users/myself/dbs/nih-cxr14-re"
tbx11k_simplified = "/Users/myself/dbs/tbx11k-simplified"
+ # classification
+ hivtb = "/Users/myself/dbs/hiv-tb"
+ indian = "/Users/myself/dbs/tbxpredict"
+ nih_cxr14 = "/Users/myself/dbs/cxr8-256px"
+ tbpoc = "/Users/myself/dbs/tb-poc"
+ tbx11k = "/Users/myself/dbs/tbx11k"
+
+ # segmentation
+ chasedb1 = "/Users/myself/dbs/chase-db1"
+ drive = "/Users/myself/dbs/drive"
+ hrf = "/Users/myself/dbs/hrf"
+ iostar = "/Users/myself/dbs/iostar/IOSTAR Vessel Segmentation Dataset"
+ stare = "/Users/myself/dbs/stare"
+ refuge = "/Users/myself/dbs/refuge"
+ drishtigs1 = "/Users/myself/dbs/drishtigs1"
+ rimoner3 = "/Users/myself/dbs/rimone/RIM-ONE r3"
+ drionsdb = "/Users/myself/dbs/drionsdb"
+ jsrt = "/Users/myself/dbs/jsrt"
+ cxr8 = "/Users/myself/dbs/cxr8-256px"
+
+ # classification and segmentation
+ montgomery = "/Users/myself/dbs/montgomery-xrayset"
+ shenzhen = "/Users/myself/dbs/shenzhen"
+
[nih_cxr14_re]
idiap_folder_structure = false # set to `true` if at Idiap
@@ -113,8 +136,8 @@ Here is an example configuration file that may be useful as a starting point:
mednet database list
- You must procure and download databases by yourself. The raw data is not
- included in this package as we are not authorised to redistribute it.
+ You must procure and download databases by yourself. **Raw data is not
+ included in this package as we are not authorised to redistribute it**.
To check whether the downloaded version is consistent with the structure
that is expected by this package, run:
@@ -124,7 +147,7 @@ Here is an example configuration file that may be useful as a starting point:
mednet database check <database_name>
-.. _mednet.libs.classification.setup.databases:
+.. _mednet.setup.databases:
Supported Databases
===================
@@ -135,7 +158,7 @@ raw data can be downloaded. The list of images in each split is available
in the source code.
-.. _mednet.libs.classification.setup.databases.tb:
+.. _mednet.setup.databases.tb:
Tuberculosis databases
~~~~~~~~~~~~~~~~~~~~~~
@@ -176,7 +199,7 @@ In addition to the splits presented in the following table, 10 folds
- 52
-.. _mednet.libs.classification.setup.databases.tb+signs:
+.. _mednet.setup.databases.tb+signs:
Tuberculosis multilabel databases
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -212,7 +235,7 @@ In addition to the splits presented in the following table, 10 folds
- 2800
-.. _mednet.libs.classification.setup.databases.tbmultilabel+signs:
+.. _mednet.setup.databases.tbmultilabel+signs:
Tuberculosis + radiological findings databases
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -236,7 +259,7 @@ and radiological findings.
- 0
-.. _mednet.libs.classification.setup.databases.signs:
+.. _mednet.setup.databases.signs:
Radiological findings databases
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -267,7 +290,7 @@ information about tuberculosis.
- 4'054
-.. _mednet.libs.classification.setup.databases.hiv-tb:
+.. _mednet.setup.databases.hiv-tb:
HIV-Tuberculosis databases
~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -294,7 +317,7 @@ Please contact the authors of these databases to have access to the data.
- 243
-.. _mednet.libs.segmentation.setup.databases.retinography:
+.. _mednet.setup.databases.retinography:
Retinography
------------
@@ -434,7 +457,7 @@ Retinography
``A0013.jpg``, which only exists in the AMD Grand-Challenge version.
-.. _mednet.libs.segmentation.setup.databases.xray:
+.. _mednet.setup.databases.xray:
X-Ray
-----
diff --git a/doc/results/index.rst b/doc/results/index.rst
index 85b646d1..8ef26967 100644
--- a/doc/results/index.rst
+++ b/doc/results/index.rst
@@ -59,9 +59,9 @@ Stratified k-folding has been used (10 folds) to generate these results.
.. tip::
To generate the following results, you first need to predict TB on each
- fold, then use the :ref:`aggregpred command <mednet.libs.common.cli>` to aggregate the
+ fold, then use the :ref:`aggregpred command <mednet.cli>` to aggregate the
predictions together, and finally evaluate this new file using the
- :ref:`compare command <mednet.libs.common.cli>`.
+ :ref:`compare command <mednet.cli>`.
Pasa and DenseNet-121 (random initialization)
"""""""""""""""""""""""""""""""""""""""""""""
@@ -113,37 +113,37 @@ Thresholds used:
:scale: 50%
:alt: Testing sets ROC curves for Pasa model trained on normalized-kfold MC
- :py:mod:`Pasa <mednet.libs.classification.config.models.pasa>`: Pasa trained on normalized-kfold MC
+ :py:mod:`Pasa <mednet.classify.config.models.pasa>`: Pasa trained on normalized-kfold MC
- .. figure:: img/compare_pasa_mc_ch_kfold_500.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for Pasa model trained on normalized-kfold MC-CH
- :py:mod:`Pasa <mednet.libs.classification.config.models.pasa>`: Pasa trained on normalized-kfold MC-CH
+ :py:mod:`Pasa <mednet.classify.config.models.pasa>`: Pasa trained on normalized-kfold MC-CH
- .. figure:: img/compare_pasa_mc_ch_in_kfold_500.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for Pasa model trained on normalized-kfold MC-CH-IN
- :py:mod:`Pasa <mednet.libs.classification.config.models.pasa>`: Pasa trained on normalized-kfold MC-CH-IN
+ :py:mod:`Pasa <mednet.classify.config.models.pasa>`: Pasa trained on normalized-kfold MC-CH-IN
* - .. figure:: img/compare_densenet_mc_kfold_2000.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for DenseNet model trained on normalized-kfold MC
- :py:mod:`DenseNet <mednet.libs.classification.config.models.densenet>`: DenseNet trained on normalized-kfold MC
+ :py:mod:`DenseNet <mednet.classify.config.models.densenet>`: DenseNet trained on normalized-kfold MC
- .. figure:: img/compare_densenet_mc_ch_kfold_2000.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for DenseNet model trained on normalized-kfold MC-CH
- :py:mod:`DenseNet <mednet.libs.classification.config.models.densenet>`: DenseNet trained on normalized-kfold MC-CH
+ :py:mod:`DenseNet <mednet.classify.config.models.densenet>`: DenseNet trained on normalized-kfold MC-CH
- .. figure:: img/compare_densenet_mc_ch_in_kfold_2000.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for DenseNet model trained on normalized-kfold MC-CH-IN
- :py:mod:`DenseNet <mednet.libs.classification.config.models.densenet>`: DenseNet trained on normalized-kfold MC-CH-IN
+ :py:mod:`DenseNet <mednet.classify.config.models.densenet>`: DenseNet trained on normalized-kfold MC-CH-IN
DenseNet-121 (pretrained on ImageNet)
"""""""""""""""""""""""""""""""""""""
@@ -180,19 +180,19 @@ Thresholds used:
:scale: 50%
:alt: Testing sets ROC curves for DenseNet model trained on normalized-kfold MC
- :py:mod:`DenseNet <mednet.libs.classification.config.models.densenet>` DenseNet trained on normalized-kfold MC
+ :py:mod:`DenseNet <mednet.classify.config.models.densenet>` DenseNet trained on normalized-kfold MC
- .. figure:: img/compare_densenetpreIN_mc_ch_kfold_600.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for DenseNet model trained on normalized-kfold MC-CH
- :py:mod:`DenseNet <mednet.libs.classification.config.models.densenet>` DenseNet trained on normalized-kfold MC-CH
+ :py:mod:`DenseNet <mednet.classify.config.models.densenet>` DenseNet trained on normalized-kfold MC-CH
- .. figure:: img/compare_densenetpreIN_mc_ch_ch_kfold_600.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for DenseNet model trained on normalized-kfold MC-CH-IN
- :py:mod:`DenseNet <mednet.libs.classification.config.models.densenet>` DenseNet trained on normalized-kfold MC-CH-IN
+ :py:mod:`DenseNet <mednet.classify.config.models.densenet>` DenseNet trained on normalized-kfold MC-CH-IN
Logistic Regression Classifier
""""""""""""""""""""""""""""""
@@ -229,19 +229,19 @@ Thresholds used:
:scale: 50%
:alt: Testing sets ROC curves for LogReg model trained on normalized-kfold MC
- :py:mod:`LogReg <mednet.libs.classification.config.models.logistic_regression>`: LogReg trained on normalized-kfold MC
+ :py:mod:`LogReg <mednet.classify.config.models.logistic_regression>`: LogReg trained on normalized-kfold MC
- .. figure:: img/compare_logreg_mc_ch_kfold_100.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for LogReg model trained on normalized-kfold MC-CH
- :py:mod:`LogReg <mednet.libs.classification.config.models.logistic_regression>`: LogReg trained on normalized-kfold MC-CH
+ :py:mod:`LogReg <mednet.classify.config.models.logistic_regression>`: LogReg trained on normalized-kfold MC-CH
- .. figure:: img/compare_logreg_mc_ch_in_kfold_100.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for LogReg model trained on normalized-kfold MC-CH-IN
- :py:mod:`LogReg <mednet.libs.classification.config.models.logistic_regression>`: LogReg trained on normalized-kfold MC-CH-IN
+ :py:mod:`LogReg <mednet.classify.config.models.logistic_regression>`: LogReg trained on normalized-kfold MC-CH-IN
DenseNet-121 (pretrained on ImageNet and NIH CXR14)
"""""""""""""""""""""""""""""""""""""""""""""""""""
@@ -278,19 +278,19 @@ Thresholds used:
:scale: 50%
:alt: Testing sets ROC curves for DenseNet model trained on normalized-kfold MC (pretrained on NIH)
- :py:mod:`DenseNet <mednet.libs.classification.config.models.densenet>`: DenseNet trained on normalized-kfold MC (pretrained on NIH)
+ :py:mod:`DenseNet <mednet.classify.config.models.densenet>`: DenseNet trained on normalized-kfold MC (pretrained on NIH)
- .. figure:: img/compare_densenetpre_mc_ch_kfold_300.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for DenseNet model trained on normalized-kfold MC-CH (pretrained on NIH)
- :py:mod:`DenseNet <mednet.libs.classification.config.models.densenet>`: DenseNet trained on normalized-kfold MC-CH (pretrained on NIH)
+ :py:mod:`DenseNet <mednet.classify.config.models.densenet>`: DenseNet trained on normalized-kfold MC-CH (pretrained on NIH)
- .. figure:: img/compare_densenetpre_mc_ch_in_kfold_300.jpg
:align: center
:scale: 50%
:alt: Testing sets ROC curves for DenseNet model trained on normalized-kfold MC-CH-IN (pretrained on NIH)
- :py:mod:`DenseNet <mednet.libs.classification.config.models.densenet>`: DenseNet trained on normalized-kfold MC-CH-IN (pretrained on NIH)
+ :py:mod:`DenseNet <mednet.classify.config.models.densenet>`: DenseNet trained on normalized-kfold MC-CH-IN (pretrained on NIH)
Global sensitivity analysis (relevance)
@@ -301,7 +301,7 @@ Model used to generate the following figures: LogReg trained on MC-CH-IN fold 0
.. tip::
Use the ``--relevance-analysis`` argument of the :ref:`predict command
- <mednet.libs.common.cli>` to generate the following plots.
+ <mednet.cli>` to generate the following plots.
* Green color: likely TB
* Orange color: Could be TB
diff --git a/doc/usage/evaluation.rst b/doc/usage/evaluation.rst
index 45519265..c318ce01 100644
--- a/doc/usage/evaluation.rst
+++ b/doc/usage/evaluation.rst
@@ -2,7 +2,7 @@
..
.. SPDX-License-Identifier: GPL-3.0-or-later
-.. _mednet.libs.classification.usage.evaluation:
+.. _mednet.usage.evaluation:
==========================
Inference and Evaluation
@@ -17,10 +17,12 @@ and produce performance figures.
Inference
---------
-In inference (or prediction) mode, we input a model, a dataset, a model checkpoint generated during training, and output
-a json file containing the prediction outputs for every input image.
+In inference (or prediction) mode, we input a model, a dataset, a model
+checkpoint generated during training, and output a json file containing the
+prediction outputs for every input image.
+
+To run inference, use the sub-command :ref:`predict <mednet.cli>`.
-To run inference, use the sub-command :ref:`predict <mednet.libs.common.cli>`.
Examples
========
@@ -38,10 +40,11 @@ Replace ``<path/to/model.ckpt>`` to a path leading to the pre-trained model.
Evaluation
----------
-In evaluation, we input predictions to generate performance summaries that help analysis of a trained model.
-The generated files are a .pdf containing various plots and a table of metrics for each dataset split.
-Evaluation is done using the :ref:`evaluate command <mednet.libs.common.cli>` followed by the json file generated during
-the inference step and a threshold.
+In evaluation, we input predictions to generate performance summaries that help
+analysis of a trained model. The generated files are a .pdf containing various
+plots and a table of metrics for each dataset split. Evaluation is done using
+the :ref:`evaluate command <mednet.cli>` followed by the json file generated
+during the inference step and a threshold.
Use ``mednet evaluate --help`` for more information.
diff --git a/doc/usage/experiment.rst b/doc/usage/experiment.rst
index 597178bf..cb29f4b1 100644
--- a/doc/usage/experiment.rst
+++ b/doc/usage/experiment.rst
@@ -2,27 +2,32 @@
..
.. SPDX-License-Identifier: GPL-3.0-or-later
-.. _mednet.libs.classification.experiment:
+.. _mednet.experiment:
==============================
Running complete experiments
==============================
-We provide an :ref:`experiment command <mednet.libs.common.cli>`
-that runs training, followed by prediction and evaluation.
-After running, you will be able to find results from model fitting,
-prediction and evaluation under a single output directory.
+We provide an :ref:`experiment command <mednet.cli>` that runs training,
+followed by prediction and evaluation. After running, you will be able to find
+results from model fitting, prediction and evaluation under a single output
+directory.
-For example, to train a pasa model on the montgomery database
-evaluate its performance and output predictions and performance curves,
-run the following:
+For example, to train a pasa model on the montgomery database evaluate its
+performance and output predictions and performance curves, run the following:
-.. code-block:: sh
+.. code:: sh
- $ mednet experiment -vv pasa montgomery
+ # classification task
+ $ mednet classify experiment -vv pasa montgomery
# check results in the "results" folder
-You may run the system on a GPU by using the ``--device=cuda:0`` option.
+ # segmentation task
+ $ mednet segment experiment -vv lwnet drive
+ # check results in the "results" folder
+
+You may run the system on a GPU by using the ``--device=cuda``, or
+``--device=mps`` option.
.. include:: ../links.rst
diff --git a/doc/usage/index.rst b/doc/usage/index.rst
index 4b643aab..e4895b14 100644
--- a/doc/usage/index.rst
+++ b/doc/usage/index.rst
@@ -2,19 +2,19 @@
..
.. SPDX-License-Identifier: GPL-3.0-or-later
-.. _mednet.libs.classification.usage:
+.. _mednet.usage:
=======
Usage
=======
This package supports a fully reproducible research experimentation cycle for
-tuberculosis detection with support for the following activities.
+medical image classification, segmentation and more.
.. figure:: img/direct_vs_indirect.png
-.. _mednet.libs.classification.usage.direct-detection:
+.. _mednet.usage.direct-detection:
Direct detection
@@ -30,7 +30,7 @@ Direct detection
thresholds can also be calculated.
-.. \_mednet.libs.classification.usage.indirect-detection:
+.. \_mednet.usage.indirect-detection:
.. Indirect detection
------------------
@@ -51,7 +51,7 @@ Direct detection
* Comparison: Use predictions results to compare performance of multiple
systems.
-We provide :ref:`command-line interfaces (CLI) <mednet.libs.common.cli>` that implement
+We provide :ref:`command-line interfaces (CLI) <mednet.cli>` that implement
each of the phases above. This interface is configurable using :ref:`clapper's
extensible configuration framework <clapper.config>`. In essence, each
command-line option may be provided as a variable with the same name in a
@@ -66,14 +66,14 @@ to an application.
may require complex Python types that cannot be synthetized in a single
input parameter.
-We provide a number of :ref:`preset configuration files <mednet.libs.classification.config>` that
+We provide a number of :ref:`preset configuration files <mednet.config>` that
can be used in one or more of the activities described in this section. Our
command-line framework allows you to refer to these preset configuration files
using special names (a.k.a. "resources"), that procure and load these for you
automatically.
-.. _mednet.libs.classification.usage.commands:
+.. _mednet.usage.commands:
Commands
--------
diff --git a/doc/usage/saliency.rst b/doc/usage/saliency.rst
index 178aca28..d433062b 100644
--- a/doc/usage/saliency.rst
+++ b/doc/usage/saliency.rst
@@ -2,63 +2,80 @@
..
.. SPDX-License-Identifier: GPL-3.0-or-later
-.. _mednet.libs.classification.usage.saliency:
+.. _mednet.usage.saliency:
==========
Saliency
==========
-A saliency map highlights areas of interest within an image. In the context of TB detection, this would be the locations in a chest X-ray image where tuberculosis is present.
+A saliency map highlights areas of interest within an image. In the context of
+TB detection, this would be the locations in a chest X-ray image where
+tuberculosis is present.
-This package provides scripts that can generate saliency maps and compute relevant metrics for interpretability purposes.
+This package provides scripts that can generate saliency maps and compute
+relevant metrics for interpretability purposes.
-Some of the scripts require the use of a database with human-annotated saliency information.
+Some of the scripts require the use of a database with human-annotated saliency
+information.
Generation
----------
-Saliency maps can be generated with the :ref:`saliency generate command <mednet.libs.common.cli>`.
-They are represented as numpy arrays of the same size as thes images, with values in the range [0-1] and saved in .npy files.
+Saliency maps can be generated with the :ref:`saliency generate command
+<mednet.cli>`. They are represented as numpy arrays of the same size as thes
+images, with values in the range [0-1] and saved in .npy files.
-Several mapping algorithms are available to choose from, which can be specified with the -s option.
+Several mapping algorithms are available to choose from, which can be specified
+with the -s option.
Examples
========
-Generates saliency maps for all prediction dataloaders on a DataModule,
-using a pre-trained pasa model, and saves them as numpy-pickeled
-objects on the output directory:
+Generates saliency maps for all prediction dataloaders on a DataModule, using a
+pre-trained pasa model, and saves them as numpy-pickeled objects on the output
+directory:
.. code:: sh
- mednet saliency generate -vv pasa tbx11k-v1-healthy-vs-atb --weight=path/to/model-at-lowest-validation-loss.ckpt --output-folder=path/to/output
+ mednet classify saliency generate -vv pasa tbx11k-v1-healthy-vs-atb --weight=path/to/model-at-lowest-validation-loss.ckpt --output-folder=path/to/output
+
Viewing
-------
-To overlay saliency maps over the original images, use the :ref:`saliency view command <mednet.libs.common.cli>`.
-Results are saved as PNG images in which brigter pixels correspond to areas with higher saliency.
+To overlay saliency maps over the original images, use the :ref:`classify
+saliency view command <mednet.cli>`. Results are saved as PNG images in which
+brigter pixels correspond to areas with higher saliency.
Examples
========
-Generates visualizations in form of heatmaps from existing saliency maps for a dataset configuration:
+Generates visualizations in form of heatmaps from existing saliency maps for a
+dataset configuration:
.. code:: sh
- # input-folder is the location of the saliency maps created with `mednet generate`
- mednet saliency view -vv pasa tbx11k-v1-healthy-vs-atb --input-folder=parent_folder/gradcam/ --output-folder=path/to/visualizations
+ # input-folder is the location of the saliency maps created with `mednet generate`
+ mednet classify saliency view -vv pasa tbx11k-v1-healthy-vs-atb --input-folder=parent_folder/gradcam/ --output-folder=path/to/visualizations
Interpretability
----------------
-Given a target label, the interpretability step computes the proportional energy and average saliency focus in a DataModule.
+Given a target label, the interpretability step computes the proportional
+energy and average saliency focus in a DataModule.
-The proportional energy is defined as the quantity of activation that lies within the ground truth boxes compared to the total sum of the activations.
-The average saliency focus is the sum of the values of the saliency map over the ground-truth bounding boxes, normalized by the total area covered by all ground-truth bounding boxes.
+The proportional energy is defined as the quantity of activation that lies
+within the ground truth boxes compared to the total sum of the activations. The
+average saliency focus is the sum of the values of the saliency map over the
+ground-truth bounding boxes, normalized by the total area covered by all
+ground-truth bounding boxes.
+
+.. note::
+
+ Currently, this functionality requires a DataModule containing
+ human-annotated bounding boxes.
-This requires a DataModule containing human-annotated bounding boxes.
Examples
========
@@ -67,36 +84,42 @@ Evaluate the generated saliency maps for their localization performance:
.. code:: sh
- mednet saliency interpretability -vv tbx11k-v1-healthy-vs-atb --input-folder=parent-folder/saliencies/ --output-json=path/to/interpretability-scores.json
+ mednet saliency interpretability -vv tbx11k-v1-healthy-vs-atb --input-folder=parent-folder/saliencies/ --output-json=path/to/interpretability-scores.json
Completeness
------------
-The saliency completeness script computes ROAD scores of saliency maps and saves them in a .json file.
-The ROAD algorithm estimates the explainability (in the completeness sense) of saliency maps by substituting
-relevant pixels in the input image by a local average, re-running prediction on the altered image,
-and measuring changes in the output classification score when said perturbations are in place.
-By substituting most or least relevant pixels with surrounding averages, the ROAD algorithm estimates
-the importance of such elements in the produced saliency map.
+The saliency completeness script computes ROAD scores of saliency maps and
+saves them in a ``.json`` file.
-More information can be found in [ROAD-2022]_.
+The ROAD algorithm ([ROAD-2022]_) estimates the explainability (in the
+completeness sense) of saliency maps by substituting relevant pixels in the
+input image by a local average, re-running prediction on the altered image, and
+measuring changes in the output classification score when said perturbations
+are in place. By substituting most or least relevant pixels with surrounding
+averages, the ROAD algorithm estimates the importance of such elements in the
+produced saliency map.
This requires a DataModule containing human-annotated bounding boxes.
+
Examples
========
-Calculates the ROAD scores for an existing dataset configuration and stores them in .json files:
+Calculates the ROAD scores for an existing dataset configuration and stores
+them in ``.json`` files:
.. code:: sh
- mednet saliency completeness -vv pasa tbx11k-v1-healthy-vs-atb --device="cuda:0" --weight=path/to/model-at-lowest-validation-loss.ckpt --output-json=path/to/completeness-scores.json
+ mednet classify saliency completeness -vv pasa tbx11k-v1-healthy-vs-atb --device="cuda:0" --weight=path/to/model-at-lowest-validation-loss.ckpt --output-json=path/to/completeness-scores.json
Evaluation
----------
-The saliency evaluation step generates tables and plots from the results of the interpretability and completeness steps.
+
+Saliency evaluation step generates tables and plots from the results of the
+interpretability and completeness steps.
Examples
========
@@ -105,6 +128,7 @@ Tabulates and generates plots for two saliency map algorithms:
.. code:: sh
- mednet saliency evaluate -vv -e gradcam path/to/gradcam-completeness.json path/to/gradcam-interpretability.json -e gradcam++ path/to/gradcam++-completeness.json path/to/gradcam++-interpretability.json
+ mednet saliency evaluate -vv -e gradcam path/to/gradcam-completeness.json path/to/gradcam-interpretability.json -e gradcam++ path/to/gradcam++-completeness.json path/to/gradcam++-interpretability.json
+
.. include:: ../links.rst
diff --git a/doc/usage/training.rst b/doc/usage/training.rst
index 380e5ef5..ae8d5612 100644
--- a/doc/usage/training.rst
+++ b/doc/usage/training.rst
@@ -2,7 +2,7 @@
..
.. SPDX-License-Identifier: GPL-3.0-or-later
-.. _mednet.libs.classification.usage.training:
+.. _mednet.usage.training:
==========
Training
@@ -68,10 +68,13 @@ To train Pasa CNN on the Montgomery dataset:
Plotting training metrics
-------------------------
-Various metrics are recorded at each epoch during training, such as the execution time, loss and resource usage.
-These are saved in a Tensorboard file, located in a `logs` subdirectory of the training output folder.
+Various metrics are recorded at each epoch during training, such as the
+execution time, loss and resource usage. These are saved in a Tensorboard file,
+located in a `logs` subdirectory of the training output folder.
+
+Mednet provides a :ref:`train-analysis <mednet.cli>` convenience script that
+graphs the scalars stored in these files and saves them in a .pdf file.
-Mednet provides a :ref:`train-analysis <mednet.libs.common.cli>` convenience script that graphs the scalars stored in these files and saves them in a .pdf file.
Examples
========
diff --git a/helpers/extract_hdf5_images.py b/helpers/extract_hdf5_images.py
index e29c84a6..93e03884 100644
--- a/helpers/extract_hdf5_images.py
+++ b/helpers/extract_hdf5_images.py
@@ -1,3 +1,6 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
import argparse
import pathlib
diff --git a/helpers/gen_histograms.sh b/helpers/gen_histograms.sh
deleted file mode 100755
index b5cbeb2e..00000000
--- a/helpers/gen_histograms.sh
+++ /dev/null
@@ -1,43 +0,0 @@
-pixi run python3 helpers/generate_histograms_classification.py alexnet -d montgomery -f default
-pixi run python3 helpers/generate_histograms_classification.py densenet -d montgomery -f default
-pixi run python3 helpers/generate_histograms_classification.py pasa -d montgomery -f default
-
-pixi run python3 helpers/generate_histograms_classification.py -d hivtb -f fold_0
-pixi run python3 helpers/generate_histograms_classification.py -d indian -f default
-pixi run python3 helpers/generate_histograms_classification.py -d montgomery -f default
-pixi run python3 helpers/generate_histograms_classification.py -d nih_cxr14 -f default
-pixi run python3 helpers/generate_histograms_classification.py -d padchest -f idiap
-pixi run python3 helpers/generate_histograms_classification.py -d shenzhen -f default
-pixi run python3 helpers/generate_histograms_classification.py -d tbpoc -f fold_0
-pixi run python3 helpers/generate_histograms_classification.py -d tbx11k_v1 -f fold_0
-pixi run python3 helpers/generate_histograms_classification.py -d tbx11k_v2 -f fold_0
-
-pixi run python3 helpers/generate_histograms_segmentation.py -d chasedb1 -f first_annotator
-pixi run python3 helpers/generate_histograms_segmentation.py -d cxr8 -f default
-pixi run python3 helpers/generate_histograms_segmentation.py -d drhagis -f default
-pixi run python3 helpers/generate_histograms_segmentation.py -d drionsdb -f expert1
-pixi run python3 helpers/generate_histograms_segmentation.py -d drishtigs1 -f optic_cup_all
-pixi run python3 helpers/generate_histograms_segmentation.py -d drive -f default
-pixi run python3 helpers/generate_histograms_segmentation.py -d hrf -f default
-pixi run python3 helpers/generate_histograms_segmentation.py -d iostar -f vessel
-pixi run python3 helpers/generate_histograms_segmentation.py -d jsrt -f default
-pixi run python3 helpers/generate_histograms_segmentation.py -d montgomery -f default
-pixi run python3 helpers/generate_histograms_segmentation.py -d refuge -f cup
-pixi run python3 helpers/generate_histograms_segmentation.py -d rimoner3 -f cup_exp1
-pixi run python3 helpers/generate_histograms_segmentation.py -d shenzhen -f default
-pixi run python3 helpers/generate_histograms_segmentation.py -d stare -f ah
-
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d chasedb1 -f first_annotator
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d cxr8 -f default
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d drhagis -f default
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d drionsdb -f expert1
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d drishtigs1 -f optic_cup_all
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d drive -f default
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d hrf -f default
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d iostar -f vessel
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d jsrt -f default
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d montgomery -f default
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d refuge -f cup
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d rimoner3 -f cup_exp1
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d shenzhen -f default
-pixi run python3 helpers/generate_histograms_segmentation.py lwnet -d stare -f ah
diff --git a/helpers/generate_histograms.py b/helpers/generate_histograms.py
index 6b69861b..b3a9ab48 100644
--- a/helpers/generate_histograms.py
+++ b/helpers/generate_histograms.py
@@ -1,3 +1,6 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
"""Script to automatically generate histograms from DataLoader samples.
!!!DO NOT USE THIS TO "FIX" TESTS!!!
@@ -17,17 +20,15 @@ import click
import matplotlib.pyplot as plt
import numpy
import PIL
+import PIL.Image
import torch
from clapper.click import ConfigCommand as _BaseConfigCommand
from clapper.click import ResourceOption
from clapper.logging import setup
-from mednet.libs.classification.scripts.database import (
- _get_raw_databases as classification_databases,
-)
-from mednet.libs.common.data.typing import Dataset
-from mednet.libs.segmentation.scripts.database import (
- _get_raw_databases as segmentation_databases,
-)
+from mednet.classify.models.classification_model import ClassificationModel
+from mednet.data.typing import Dataset
+from mednet.scripts.database import _get_raw_databases as get_raw_databases
+from mednet.segment.models.segmentation_model import SegmentationModel
from torchvision.transforms.functional import to_pil_image
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
@@ -86,7 +87,7 @@ def prettify_json(data: str):
return re.sub(r"\]}", "\n ]\n}\n", prettified)
-def display_histogram(sample_path: pathlib.Path, image: PIL.Image, histogram):
+def display_histogram(sample_path: pathlib.Path, image: PIL.Image.Image, histogram):
color_values = range(256)
_, ax = plt.subplot_mosaic([["tbx", "histogram"]], figsize=(7, 3.5))
@@ -167,6 +168,9 @@ def get_histograms_for_split(
current_sample = data[index]
image_data = current_sample[0]
+ if isinstance(image_data, dict):
+ image_data = image_data["image"]
+
sample_path = current_sample[1]["name"]
histogram = compute_histogram_from_image_tensor(image_data)
@@ -187,7 +191,7 @@ def get_histograms_for_split(
@click.command(
- entry_point_group="mednet.libs.segmentation.config",
+ entry_point_group="mednet.config",
cls=ConfigCommand,
)
@click.option(
@@ -261,13 +265,7 @@ def main(
**_,
):
random.seed(seed)
-
- if library == "classification":
- config = classification_databases()
- elif library == "segmentation":
- config = segmentation_databases()
- else:
- raise ValueError(f"No such library: {library}")
+ config = get_raw_databases()
databases_to_use = {}
if database is not None:
@@ -290,41 +288,57 @@ def main(
# this database does not have a "datadir"
continue
- if v["datadir"] is not None:
- try:
- datamodule = importlib.import_module(
- f".{fold_name}", f"mednet.libs.segmentation.config.data.{k}"
- ).datamodule
- except ModuleNotFoundError as e:
- print(e)
+ if v["datadir"] is None:
+ # the datadir of this database is not configured
+ print(f"Skipping {k} as database is not installed.")
+ continue
+
+ if isinstance(model, ClassificationModel):
+ module_paths = [m for m in v["module"] if "classify" in m]
+ if len(module_paths) == 0:
+ print(f"Skipping {k} (not a classification database?)")
+ continue
+ module_path = module_paths[0]
+ elif isinstance(model, SegmentationModel):
+ module_paths = [m for m in v["module"] if "segment" in m]
+ if len(module_paths) == 0:
+ print(f"Skipping {k} (not a segmentation database?)")
continue
+ module_path = module_paths[0]
+ else:
+ print(f"Model type ({type(model)}) is not supported.")
+ continue
- output_dir = pathlib.Path(
- f"{library}_histograms{model_name}_{k}_{fold_name}"
- )
- images_subdir = output_dir / "images"
- if not output_dir.exists():
- output_dir.mkdir(parents=True, exist_ok=True)
+ try:
+ datamodule = importlib.import_module(
+ f".{fold_name}", module_path
+ ).datamodule
+ except ModuleNotFoundError as e:
+ print(e)
+ continue
- output_file = output_dir / f"histograms{model_name}_{k}_{fold_name}.json"
+ output_dir = pathlib.Path(f"{library}_histograms{model_name}_{k}_{fold_name}")
+ images_subdir = output_dir / "images"
+ if not output_dir.exists():
+ output_dir.mkdir(parents=True, exist_ok=True)
- output_json_data = {}
+ output_file = output_dir / f"histograms{model_name}_{k}_{fold_name}.json"
- datamodule.model_transforms = model_transforms
- datamodule.setup("predict")
+ output_json_data = {}
- for split_name, dataset_data in datamodule._datasets.items(): # noqa: SLF001
- output_json_data[split_name] = get_histograms_for_split(
- dataset_data, num_histograms, images_subdir, debug
- )
+ datamodule.model_transforms = model_transforms
+ datamodule.setup("predict")
- output_json_data = prettify_json(output_json_data)
+ for split_name, dataset_data in datamodule._datasets.items(): # noqa: SLF001
+ output_json_data[split_name] = get_histograms_for_split(
+ dataset_data, num_histograms, images_subdir, debug
+ )
- with output_file.open("w") as o_f:
- o_f.write(output_json_data)
- print(f"Saved histogram for {k} at {output_file}")
- else:
- print(f"Skipping {k} as database is not installed.")
+ output_json_data = prettify_json(output_json_data)
+
+ with output_file.open("w") as o_f:
+ o_f.write(output_json_data)
+ print(f"Saved histogram for {k} at {output_file}")
if __name__ == "__main__":
diff --git a/helpers/generate_histograms.sh b/helpers/generate_histograms.sh
new file mode 100755
index 00000000..3e694e52
--- /dev/null
+++ b/helpers/generate_histograms.sh
@@ -0,0 +1,48 @@
+#!/usr/bin/env sh
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+pixi run python3 helpers/generate_histograms.py alexnet -d montgomery -f default
+pixi run python3 helpers/generate_histograms.py densenet -d montgomery -f default
+pixi run python3 helpers/generate_histograms.py pasa -d montgomery -f default
+
+pixi run python3 helpers/generate_histograms.py -d hivtb -f fold_0
+pixi run python3 helpers/generate_histograms.py -d indian -f default
+pixi run python3 helpers/generate_histograms.py -d montgomery -f default
+pixi run python3 helpers/generate_histograms.py -d nih_cxr14 -f default
+pixi run python3 helpers/generate_histograms.py -d padchest -f idiap
+pixi run python3 helpers/generate_histograms.py -d shenzhen -f default
+pixi run python3 helpers/generate_histograms.py -d tbpoc -f fold_0
+pixi run python3 helpers/generate_histograms.py -d tbx11k_v1 -f fold_0
+pixi run python3 helpers/generate_histograms.py -d tbx11k_v2 -f fold_0
+
+pixi run python3 helpers/generate_histograms.py -d chasedb1 -f first_annotator
+pixi run python3 helpers/generate_histograms.py -d cxr8 -f default
+pixi run python3 helpers/generate_histograms.py -d drhagis -f default
+pixi run python3 helpers/generate_histograms.py -d drionsdb -f expert1
+pixi run python3 helpers/generate_histograms.py -d drishtigs1 -f optic_cup_all
+pixi run python3 helpers/generate_histograms.py -d drive -f default
+pixi run python3 helpers/generate_histograms.py -d hrf -f default
+pixi run python3 helpers/generate_histograms.py -d iostar -f vessel
+pixi run python3 helpers/generate_histograms.py -d jsrt -f default
+pixi run python3 helpers/generate_histograms.py -d montgomery -f default
+pixi run python3 helpers/generate_histograms.py -d refuge -f cup
+pixi run python3 helpers/generate_histograms.py -d rimoner3 -f cup_exp1
+pixi run python3 helpers/generate_histograms.py -d shenzhen -f default
+pixi run python3 helpers/generate_histograms.py -d stare -f ah
+
+pixi run python3 helpers/generate_histograms.py lwnet -d chasedb1 -f first_annotator
+pixi run python3 helpers/generate_histograms.py lwnet -d cxr8 -f default
+pixi run python3 helpers/generate_histograms.py lwnet -d drhagis -f default
+pixi run python3 helpers/generate_histograms.py lwnet -d drionsdb -f expert1
+pixi run python3 helpers/generate_histograms.py lwnet -d drishtigs1 -f optic_cup_all
+pixi run python3 helpers/generate_histograms.py lwnet -d drive -f default
+pixi run python3 helpers/generate_histograms.py lwnet -d hrf -f default
+pixi run python3 helpers/generate_histograms.py lwnet -d iostar -f vessel
+pixi run python3 helpers/generate_histograms.py lwnet -d jsrt -f default
+pixi run python3 helpers/generate_histograms.py lwnet -d montgomery -f default
+pixi run python3 helpers/generate_histograms.py lwnet -d refuge -f cup
+pixi run python3 helpers/generate_histograms.py lwnet -d rimoner3 -f cup_exp1
+pixi run python3 helpers/generate_histograms.py lwnet -d shenzhen -f default
+pixi run python3 helpers/generate_histograms.py lwnet -d stare -f ah
diff --git a/helpers/generate_histograms_classification.py b/helpers/generate_histograms_classification.py
deleted file mode 100644
index abb66807..00000000
--- a/helpers/generate_histograms_classification.py
+++ /dev/null
@@ -1,307 +0,0 @@
-"""Script to automatically generate histograms from DataLoader samples.
-
-!!!DO NOT USE THIS TO "FIX" TESTS!!!
-If a test fails because the expected histogram is different than the reference
-histogram generated by this, make sure it is not an issue with the code first.
-A valid reason to re-generate histograms would be a change in the applied transforms.
-"""
-
-import importlib
-import json
-import pathlib
-import random
-import re
-from typing import TypeAlias
-
-import click
-import matplotlib.pyplot as plt
-import numpy
-import PIL
-import torch
-from clapper.click import ConfigCommand as _BaseConfigCommand
-from clapper.click import ResourceOption
-from clapper.logging import setup
-from mednet.libs.classification.scripts.database import (
- _get_raw_databases as classification_databases,
-)
-from mednet.libs.common.data.typing import Dataset
-from torchvision.transforms.functional import to_pil_image
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-Histogram: TypeAlias = list[int]
-
-
-class ConfigCommand(_BaseConfigCommand):
- """A click command-class that has the properties of
- :py:class:`clapper.click.ConfigCommand` and adds verbatim epilog
- formatting.
- """
-
- def format_epilog(
- self, _: click.core.Context, formatter: click.formatting.HelpFormatter
- ) -> None:
- """Format the command epilog during --help.
-
- Parameters
- ----------
- _
- The current parsing context.
- formatter
- The formatter to use for printing text.
- """
-
- if self.epilog:
- formatter.write_paragraph()
- for line in self.epilog.split("\n"):
- formatter.write(line + "\n")
-
-
-def prettify_json(data: str):
- """Prettify function, in order to reduce file size and not having to rely on external tools.
-
- Parameters
- ----------
- data
- The json data to prettify.
-
- Returns
- -------
- The prettified json data.
- """
- prettified = json.dumps(data)
- # Opening bracket
- prettified = re.sub(r'{"', '{\n "', prettified)
- # Carriage return after dictionary key
- prettified = re.sub(r'": \[', '": [\n ', prettified)
- # Carriage returns before new dictionary key
- prettified = re.sub(r'\]\], "', ']\n ],\n "', prettified)
- # Carriage return after end of sample
- prettified = re.sub(r'\], \["', '],\n ["', prettified)
- # Ending brackets
- return re.sub(r"\]}", "\n ]\n}\n", prettified)
-
-
-def display_histogram(sample_path: pathlib.Path, image: PIL.Image, histogram):
- color_values = range(256)
-
- _, ax = plt.subplot_mosaic([["tbx", "histogram"]], figsize=(7, 3.5))
-
- ax["tbx"].imshow(image, cmap="gray", vmin=0, vmax=255)
- ax["tbx"].axis("off")
-
- ax["histogram"].plot(color_values, histogram)
-
- print(sample_path)
- plt.show()
- # import pdb; pdb.set_trace()
-
-
-def compute_histogram_from_image_tensor(
- image_tensor: torch.Tensor,
-) -> Histogram:
- """Compute the histogram from a Tensor containing image data.
-
- Parameters
- ----------
- image_tensor
- The tensor from which to compute the histogram. Expected size [num_channels, width, height].
-
- Returns
- -------
- The computed histogram, of length num_channels * width * height. The channels are in RGB order.
- """
- channels_histograms = []
- for color_channel in image_tensor:
- color_channel = numpy.multiply(color_channel.numpy(), 255).astype(int)
- histogram = numpy.histogram(color_channel, bins=256, range=(0, 256))
- # Note that the image channels are concatenated
- channels_histograms.extend(histogram[0].tolist())
-
- return channels_histograms
-
-
-def get_histograms_for_split(
- data: Dataset,
- num_histograms: int,
- images_subdir: pathlib.Path,
- debug: bool = False,
-) -> list[tuple[pathlib.Path, Histogram]]:
- """Compute the histograms for samples in a database split and saves the samples after transformations have been applied for manual verification.
-
- Parameters
- ----------
- data
- A mednet Dataset instance.
- num_histograms
- The number of histograms to generate per split.
- Setting a value of 0 will conpute a histogram for every sample in the split.
- images_subdir
- Directory in which to save the samples with transforms applied.
- debug
- If set to True, will open a window with the transformed image and corresponding histogram for each sample.
-
- Returns
- -------
- A list of path to samples and corresponding histograms.
- """
- computed_histograms = []
- sample_indexes: list[int] = []
-
- # Compute histograms for entire dataset if num_histograms is set to 0
- if num_histograms == 0:
- sample_indexes = list(range(len(data)))
- else:
- for _ in range(num_histograms):
- sample_indexes.append(random.randint(0, len(data) - 1))
-
- for index in sample_indexes:
- current_sample = data[index]
-
- image_data = current_sample[0]
- sample_path = current_sample[1]["name"]
- histogram = compute_histogram_from_image_tensor(image_data)
-
- image_path = images_subdir / sample_path
- if not image_path.parent.exists():
- image_path.parent.mkdir(parents=True, exist_ok=True)
-
- img = to_pil_image(image_data)
- img.save(image_path.with_suffix(".png"))
-
- computed_histograms.append((sample_path, histogram))
-
- if debug:
- display_histogram(sample_path, img, histogram)
-
- return computed_histograms
-
-
-@click.command(
- entry_point_group="mednet.libs.classification.config",
- cls=ConfigCommand,
-)
-@click.option(
- "--model",
- "-m",
- help="""A lightning module instance implementing the network architecture
- (not the weights, necessarily) to be used for prediction.""",
- required=False,
- cls=ResourceOption,
-)
-@click.option(
- "--database",
- "-d",
- help="""The name of the database to use for generating the histograms. If not specified, tries all available databases.""",
- required=False,
- type=str,
- cls=ResourceOption,
-)
-@click.option(
- "--fold-name",
- "-f",
- help="""The name of the fold to use for generating the histograms.""",
- required=False,
- default="default",
- type=str,
- cls=ResourceOption,
-)
-@click.option(
- "--num-histograms",
- "-n",
- help="""The number of histograms to generate per split.""",
- required=False,
- default=5,
- type=int,
- cls=ResourceOption,
-)
-@click.option(
- "--seed",
- "-s",
- help="""The seed number to initialize the RNG with.""",
- required=False,
- default=42,
- type=int,
- cls=ResourceOption,
-)
-@click.option(
- "--debug",
- help="""If true, opens a window with the sample and the histogram(s) side by side after each computation.""",
- required=False,
- type=bool,
- cls=ResourceOption,
-)
-def main(
- model,
- database,
- num_histograms,
- fold_name,
- seed,
- debug,
- **_,
-):
- random.seed(seed)
-
- library = "classification"
- config = classification_databases()
-
- databases_to_use = {}
- if database is not None:
- databases_to_use[database] = config[database]
- else:
- databases_to_use = config
-
- model_transforms = []
-
- model_name = ""
- if model is not None:
- model_name = f"_{model.name}"
- model_transforms = model.model_transforms
- print(f"Loaded model transforms from {model.name}")
-
- for k, v in databases_to_use.items():
- print(f"Processing database {k}")
-
- if "datadir" not in v:
- # this database does not have a "datadir"
- continue
-
- if v["datadir"] is not None:
- try:
- datamodule = importlib.import_module(
- f".{fold_name}", f"mednet.libs.classification.config.data.{k}"
- ).datamodule
- except ModuleNotFoundError as e:
- print(e)
- continue
-
- output_dir = pathlib.Path(
- f"{library}_histograms{model_name}_{k}_{fold_name}"
- )
- images_subdir = output_dir / "images"
- if not output_dir.exists():
- output_dir.mkdir(parents=True, exist_ok=True)
-
- output_file = output_dir / f"histograms{model_name}_{k}_{fold_name}.json"
-
- output_json_data = {}
-
- datamodule.model_transforms = model_transforms
- datamodule.setup("predict")
-
- for split_name, dataset_data in datamodule._datasets.items(): # noqa: SLF001
- output_json_data[split_name] = get_histograms_for_split(
- dataset_data, num_histograms, images_subdir, debug
- )
-
- output_json_data = prettify_json(output_json_data)
-
- with output_file.open("w") as o_f:
- o_f.write(output_json_data)
- print(f"Saved histogram for {k} at {output_file}")
- else:
- print(f"Skipping {k} as database is not installed.")
-
-
-if __name__ == "__main__":
- main()
diff --git a/helpers/generate_histograms_segmentation.py b/helpers/generate_histograms_segmentation.py
deleted file mode 100644
index 0356b2cb..00000000
--- a/helpers/generate_histograms_segmentation.py
+++ /dev/null
@@ -1,308 +0,0 @@
-"""Script to automatically generate histograms from DataLoader samples.
-
-!!!DO NOT USE THIS TO "FIX" TESTS!!!
-If a test fails because the expected histogram is different than the reference
-histogram generated by this, make sure it is not an issue with the code first.
-A valid reason to re-generate histograms would be a change in the applied transforms.
-"""
-
-import importlib
-import json
-import pathlib
-import random
-import re
-from typing import TypeAlias
-
-import click
-import matplotlib.pyplot as plt
-import numpy
-import PIL
-import torch
-from clapper.click import ConfigCommand as _BaseConfigCommand
-from clapper.click import ResourceOption
-from clapper.logging import setup
-from mednet.libs.common.data.typing import Dataset
-from mednet.libs.segmentation.scripts.database import (
- _get_raw_databases as segmentation_databases,
-)
-from torchvision.transforms.functional import to_pil_image
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-Histogram: TypeAlias = list[int]
-
-
-class ConfigCommand(_BaseConfigCommand):
- """A click command-class that has the properties of
- :py:class:`clapper.click.ConfigCommand` and adds verbatim epilog
- formatting.
- """
-
- def format_epilog(
- self, _: click.core.Context, formatter: click.formatting.HelpFormatter
- ) -> None:
- """Format the command epilog during --help.
-
- Parameters
- ----------
- _
- The current parsing context.
- formatter
- The formatter to use for printing text.
- """
-
- if self.epilog:
- formatter.write_paragraph()
- for line in self.epilog.split("\n"):
- formatter.write(line + "\n")
-
-
-def prettify_json(data: str):
- """Prettify function, in order to reduce file size and not having to rely on external tools.
-
- Parameters
- ----------
- data
- The json data to prettify.
-
- Returns
- -------
- The prettified json data.
- """
- prettified = json.dumps(data)
- # Opening bracket
- prettified = re.sub(r'{"', '{\n "', prettified)
- # Carriage return after dictionary key
- prettified = re.sub(r'": \[', '": [\n ', prettified)
- # Carriage returns before new dictionary key
- prettified = re.sub(r'\]\], "', ']\n ],\n "', prettified)
- # Carriage return after end of sample
- prettified = re.sub(r'\], \["', '],\n ["', prettified)
- # Ending brackets
- return re.sub(r"\]}", "\n ]\n}\n", prettified)
-
-
-def display_histogram(sample_path: pathlib.Path, image: PIL.Image, histogram):
- color_values = range(256)
-
- _, ax = plt.subplot_mosaic([["tbx", "histogram"]], figsize=(7, 3.5))
-
- ax["tbx"].imshow(image, cmap="gray", vmin=0, vmax=255)
- ax["tbx"].axis("off")
-
- ax["histogram"].plot(color_values, histogram)
-
- print(sample_path)
- plt.show()
- # import pdb; pdb.set_trace()
-
-
-def compute_histogram_from_image_tensor(
- image_tensor: torch.Tensor,
-) -> Histogram:
- """Compute the histogram from a Tensor containing image data.
-
- Parameters
- ----------
- image_tensor
- The tensor from which to compute the histogram. Expected size [num_channels, width, height].
-
- Returns
- -------
- The computed histogram, of length num_channels * width * height. The channels are in RGB order.
- """
- channels_histograms = []
- for color_channel in image_tensor:
- color_channel = numpy.multiply(color_channel.numpy(), 255).astype(int)
- histogram = numpy.histogram(color_channel, bins=256, range=(0, 256))
- # Note that the image channels are concatenated
- channels_histograms.extend(histogram[0].tolist())
-
- return channels_histograms
-
-
-def get_histograms_for_split(
- data: Dataset,
- num_histograms: int,
- images_subdir: pathlib.Path,
- debug: bool = False,
-) -> list[tuple[pathlib.Path, Histogram]]:
- """Compute the histograms for samples in a database split and saves the samples after transformations have been applied for manual verification.
-
- Parameters
- ----------
- data
- A mednet Dataset instance.
- num_histograms
- The number of histograms to generate per split.
- Setting a value of 0 will conpute a histogram for every sample in the split.
- images_subdir
- Directory in which to save the samples with transforms applied.
- debug
- If set to True, will open a window with the transformed image and corresponding histogram for each sample.
-
- Returns
- -------
- A list of path to samples and corresponding histograms.
- """
- computed_histograms = []
- sample_indexes: list[int] = []
-
- # Compute histograms for entire dataset if num_histograms is set to 0
- if num_histograms == 0:
- sample_indexes = list(range(len(data)))
- else:
- for _ in range(num_histograms):
- sample_indexes.append(random.randint(0, len(data) - 1))
-
- for index in sample_indexes:
- current_sample = data[index]
-
- image_data = current_sample[0]["image"]
- sample_path = current_sample[1]["name"]
-
- histogram = compute_histogram_from_image_tensor(image_data)
-
- image_path = images_subdir / sample_path
- if not image_path.parent.exists():
- image_path.parent.mkdir(parents=True, exist_ok=True)
-
- img = to_pil_image(image_data)
- img.save(image_path.with_suffix(".png"))
-
- computed_histograms.append((sample_path, histogram))
-
- if debug:
- display_histogram(sample_path, img, histogram)
-
- return computed_histograms
-
-
-@click.command(
- entry_point_group="mednet.libs.segmentation.config",
- cls=ConfigCommand,
-)
-@click.option(
- "--model",
- "-m",
- help="""A lightning module instance implementing the network architecture
- (not the weights, necessarily) to be used for prediction.""",
- required=False,
- cls=ResourceOption,
-)
-@click.option(
- "--database",
- "-d",
- help="""The name of the database to use for generating the histograms. If not specified, tries all available databases.""",
- required=False,
- type=str,
- cls=ResourceOption,
-)
-@click.option(
- "--fold-name",
- "-f",
- help="""The name of the fold to use for generating the histograms.""",
- required=False,
- default="default",
- type=str,
- cls=ResourceOption,
-)
-@click.option(
- "--num-histograms",
- "-n",
- help="""The number of histograms to generate per split.""",
- required=False,
- default=5,
- type=int,
- cls=ResourceOption,
-)
-@click.option(
- "--seed",
- "-s",
- help="""The seed number to initialize the RNG with.""",
- required=False,
- default=42,
- type=int,
- cls=ResourceOption,
-)
-@click.option(
- "--debug",
- help="""If true, opens a window with the sample and the histogram(s) side by side after each computation.""",
- required=False,
- type=bool,
- cls=ResourceOption,
-)
-def main(
- model,
- database,
- num_histograms,
- fold_name,
- seed,
- debug,
- **_,
-):
- random.seed(seed)
-
- library = "segmentation"
- config = segmentation_databases()
-
- databases_to_use = {}
- if database is not None:
- databases_to_use[database] = config[database]
- else:
- databases_to_use = config
-
- model_transforms = []
-
- model_name = ""
- if model is not None:
- model_name = f"_{model.name}"
- model_transforms = model.model_transforms
- print(f"Loaded model transforms from {model.name}")
-
- for k, v in databases_to_use.items():
- print(f"Processing database {k}")
-
- if "datadir" not in v:
- # this database does not have a "datadir"
- continue
-
- if v["datadir"] is not None:
- try:
- datamodule = importlib.import_module(
- f".{fold_name}", f"mednet.libs.segmentation.config.data.{k}"
- ).datamodule
- except ModuleNotFoundError as e:
- print(e)
- continue
-
- output_dir = pathlib.Path(
- f"{library}_histograms{model_name}_{k}_{fold_name}"
- )
- images_subdir = output_dir / "images"
- if not output_dir.exists():
- output_dir.mkdir(parents=True, exist_ok=True)
-
- output_file = output_dir / f"histograms{model_name}_{k}_{fold_name}.json"
-
- output_json_data = {}
-
- datamodule.model_transforms = model_transforms
- datamodule.setup("predict")
-
- for split_name, dataset_data in datamodule._datasets.items(): # noqa: SLF001
- output_json_data[split_name] = get_histograms_for_split(
- dataset_data, num_histograms, images_subdir, debug
- )
-
- output_json_data = prettify_json(output_json_data)
-
- with output_file.open("w") as o_f:
- o_f.write(output_json_data)
- print(f"Saved histogram for {k} at {output_file}")
- else:
- print(f"Skipping {k} as database is not installed.")
-
-
-if __name__ == "__main__":
- main()
diff --git a/helpers/montgomery_preprocess.py b/helpers/montgomery_preprocess.py
index f7b5f4fe..399c524b 100644
--- a/helpers/montgomery_preprocess.py
+++ b/helpers/montgomery_preprocess.py
@@ -12,8 +12,8 @@ import sys
import numpy
import PIL.Image
-from mednet.libs.common.data.image_utils import remove_black_borders
-from mednet.libs.common.models.transforms import square_center_pad
+from mednet.data.image_utils import remove_black_borders
+from mednet.models.transforms import square_center_pad
from torch.nn.functional import interpolate
from torchvision.transforms.functional import resize, to_pil_image, to_tensor
diff --git a/helpers/tbx11k_make_splits.py b/helpers/tbx11k_make_splits.py
index 75d4d2c3..620598f2 100644
--- a/helpers/tbx11k_make_splits.py
+++ b/helpers/tbx11k_make_splits.py
@@ -2,7 +2,7 @@
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Converts TBX11k JSON annotation files into simplified JSON datasets for
-mednet.libs.classification.
+mednet.classify.
Requires ``datadir.tbx11k`` to be set on your configuration file, or that you
are sitting at the root directory of the database.
@@ -413,10 +413,7 @@ def main():
from clapper.rc import UserDefaults
datadir = pathlib.Path(
- UserDefaults("mednet.libs.classification.toml").get(
- "datadir.tbx11k",
- os.path.realpath(os.curdir),
- ),
+ UserDefaults("mednet.toml").get("datadir.tbx11k", os.path.realpath(os.curdir)),
)
train_filename = datadir / "annotations" / "json" / "TBX11K_train.json"
val_filename = datadir / "annotations" / "json" / "TBX11K_val.json"
diff --git a/helpers/visceral_preprocess.py b/helpers/visceral_preprocess.py
index 3391f512..e865014d 100644
--- a/helpers/visceral_preprocess.py
+++ b/helpers/visceral_preprocess.py
@@ -2,18 +2,25 @@
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Preprocess visceral dataset to prepare volume cubes for organ classification using 3D cnn.
-Example of use: 'python visceral_preprocess.py /idiap/temp/ojimenez/previous-projects/VISCERAL /idiap/home/ypannatier/visceral/preprocessed 237 16 '.
+
+Example of use: 'python visceral_preprocess.py
+/idiap/temp/ojimenez/previous-projects/VISCERAL
+/idiap/home/ypannatier/visceral/preprocessed 237 16 '.
Arguments of the scripts are as follow:
+
root-of-visceral-dataset
Full path to the root of the visceral dataset.
output_folder_path
Full path to the folder where the prepared cubes will be saved.
- Note that the script will create a subfolder corresponding to the desired size of cube to avoid mixing volumes of different sizes.
+ Note that the script will create a subfolder corresponding to the
+ desired size of cube to avoid mixing volumes of different sizes.
organ_id
- Integer representing the ID of the organ to process in the visceral dataset. For example, 237 corresponds to bladder.
+ Integer representing the ID of the organ to process in the visceral
+ dataset. For example, 237 corresponds to bladder.
size
- Integer representing the size of the volume cube that will be output. Each volume will be of dimension SIZExSIZExSIZE.
+ Integer representing the size of the volume cube that will be output.
+ Each volume will be of dimension SIZExSIZExSIZE.
"""
import os
diff --git a/pyproject.toml b/pyproject.toml
index b190ca3b..d319b283 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -237,259 +237,247 @@ include = [
[tool.hatch.build.targets.wheel]
packages = ["src/mednet"]
-[project.entry-points."mednet.libs.classification.config"]
+[project.entry-points."mednet.config"]
# models
-pasa = "mednet.libs.classification.config.models.pasa"
-mlp = "mednet.libs.classification.config.models.mlp"
-logistic-regression = "mednet.libs.classification.config.models.logistic_regression"
-alexnet = "mednet.libs.classification.config.models.alexnet"
-alexnet-pretrained = "mednet.libs.classification.config.models.alexnet_pretrained"
-densenet = "mednet.libs.classification.config.models.densenet"
-densenet-pretrained = "mednet.libs.classification.config.models.densenet_pretrained"
-
-# 3D models
-cnn3d = "mednet.libs.classification.config.models.cnn3d"
-
-# lists of data augmentations
-affine = "mednet.libs.common.config.augmentations.affine"
-elastic = "mednet.libs.common.config.augmentations.elastic"
-hflip = "mednet.libs.common.config.augmentations.hflip"
-jitter = "mednet.libs.common.config.augmentations.jitter"
-hflip-affine = "mednet.libs.common.config.augmentations.hflip_affine"
-hflip-jitter-affine = "mednet.libs.common.config.augmentations.hflip_jitter_affine"
+pasa = "mednet.classify.config.models.pasa"
+mlp = "mednet.classify.config.models.mlp"
+logistic-regression = "mednet.classify.config.models.logistic_regression"
+alexnet = "mednet.classify.config.models.alexnet"
+alexnet-pretrained = "mednet.classify.config.models.alexnet_pretrained"
+densenet = "mednet.classify.config.models.densenet"
+densenet-pretrained = "mednet.classify.config.models.densenet_pretrained"
+cnn3d = "mednet.classify.config.models.cnn3d"
+
+driu = "mednet.segment.config.models.driu"
+driu-bn = "mednet.segment.config.models.driu_bn"
+driu-od = "mednet.segment.config.models.driu_od"
+driu-pix = "mednet.segment.config.models.driu_pix"
+hed = "mednet.segment.config.models.hed"
+lwnet = "mednet.segment.config.models.lwnet"
+m2unet = "mednet.segment.config.models.m2unet"
+unet = "mednet.segment.config.models.unet"
+
+# lists of data augmentations (applicable to any pipeline)
+affine = "mednet.config.augmentations.affine"
+elastic = "mednet.config.augmentations.elastic"
+hflip = "mednet.config.augmentations.hflip"
+jitter = "mednet.config.augmentations.jitter"
+hflip-affine = "mednet.config.augmentations.hflip_affine"
+hflip-jitter-affine = "mednet.config.augmentations.hflip_jitter_affine"
# montgomery dataset (and cross-validation folds)
-montgomery = "mednet.libs.classification.config.data.montgomery.default"
-montgomery-f0 = "mednet.libs.classification.config.data.montgomery.fold_0"
-montgomery-f1 = "mednet.libs.classification.config.data.montgomery.fold_1"
-montgomery-f2 = "mednet.libs.classification.config.data.montgomery.fold_2"
-montgomery-f3 = "mednet.libs.classification.config.data.montgomery.fold_3"
-montgomery-f4 = "mednet.libs.classification.config.data.montgomery.fold_4"
-montgomery-f5 = "mednet.libs.classification.config.data.montgomery.fold_5"
-montgomery-f6 = "mednet.libs.classification.config.data.montgomery.fold_6"
-montgomery-f7 = "mednet.libs.classification.config.data.montgomery.fold_7"
-montgomery-f8 = "mednet.libs.classification.config.data.montgomery.fold_8"
-montgomery-f9 = "mednet.libs.classification.config.data.montgomery.fold_9"
+montgomery = "mednet.classify.config.data.montgomery.default"
+montgomery-f0 = "mednet.classify.config.data.montgomery.fold_0"
+montgomery-f1 = "mednet.classify.config.data.montgomery.fold_1"
+montgomery-f2 = "mednet.classify.config.data.montgomery.fold_2"
+montgomery-f3 = "mednet.classify.config.data.montgomery.fold_3"
+montgomery-f4 = "mednet.classify.config.data.montgomery.fold_4"
+montgomery-f5 = "mednet.classify.config.data.montgomery.fold_5"
+montgomery-f6 = "mednet.classify.config.data.montgomery.fold_6"
+montgomery-f7 = "mednet.classify.config.data.montgomery.fold_7"
+montgomery-f8 = "mednet.classify.config.data.montgomery.fold_8"
+montgomery-f9 = "mednet.classify.config.data.montgomery.fold_9"
# shenzhen dataset (and cross-validation folds)
-shenzhen = "mednet.libs.classification.config.data.shenzhen.default"
-shenzhen-alltest = "mednet.libs.classification.config.data.shenzhen.alltest"
-shenzhen-f0 = "mednet.libs.classification.config.data.shenzhen.fold_0"
-shenzhen-f1 = "mednet.libs.classification.config.data.shenzhen.fold_1"
-shenzhen-f2 = "mednet.libs.classification.config.data.shenzhen.fold_2"
-shenzhen-f3 = "mednet.libs.classification.config.data.shenzhen.fold_3"
-shenzhen-f4 = "mednet.libs.classification.config.data.shenzhen.fold_4"
-shenzhen-f5 = "mednet.libs.classification.config.data.shenzhen.fold_5"
-shenzhen-f6 = "mednet.libs.classification.config.data.shenzhen.fold_6"
-shenzhen-f7 = "mednet.libs.classification.config.data.shenzhen.fold_7"
-shenzhen-f8 = "mednet.libs.classification.config.data.shenzhen.fold_8"
-shenzhen-f9 = "mednet.libs.classification.config.data.shenzhen.fold_9"
+shenzhen = "mednet.classify.config.data.shenzhen.default"
+shenzhen-alltest = "mednet.classify.config.data.shenzhen.alltest"
+shenzhen-f0 = "mednet.classify.config.data.shenzhen.fold_0"
+shenzhen-f1 = "mednet.classify.config.data.shenzhen.fold_1"
+shenzhen-f2 = "mednet.classify.config.data.shenzhen.fold_2"
+shenzhen-f3 = "mednet.classify.config.data.shenzhen.fold_3"
+shenzhen-f4 = "mednet.classify.config.data.shenzhen.fold_4"
+shenzhen-f5 = "mednet.classify.config.data.shenzhen.fold_5"
+shenzhen-f6 = "mednet.classify.config.data.shenzhen.fold_6"
+shenzhen-f7 = "mednet.classify.config.data.shenzhen.fold_7"
+shenzhen-f8 = "mednet.classify.config.data.shenzhen.fold_8"
+shenzhen-f9 = "mednet.classify.config.data.shenzhen.fold_9"
# indian dataset (and cross-validation folds)
-indian = "mednet.libs.classification.config.data.indian.default"
-indian-f0 = "mednet.libs.classification.config.data.indian.fold_0"
-indian-f1 = "mednet.libs.classification.config.data.indian.fold_1"
-indian-f2 = "mednet.libs.classification.config.data.indian.fold_2"
-indian-f3 = "mednet.libs.classification.config.data.indian.fold_3"
-indian-f4 = "mednet.libs.classification.config.data.indian.fold_4"
-indian-f5 = "mednet.libs.classification.config.data.indian.fold_5"
-indian-f6 = "mednet.libs.classification.config.data.indian.fold_6"
-indian-f7 = "mednet.libs.classification.config.data.indian.fold_7"
-indian-f8 = "mednet.libs.classification.config.data.indian.fold_8"
-indian-f9 = "mednet.libs.classification.config.data.indian.fold_9"
+indian = "mednet.classify.config.data.indian.default"
+indian-f0 = "mednet.classify.config.data.indian.fold_0"
+indian-f1 = "mednet.classify.config.data.indian.fold_1"
+indian-f2 = "mednet.classify.config.data.indian.fold_2"
+indian-f3 = "mednet.classify.config.data.indian.fold_3"
+indian-f4 = "mednet.classify.config.data.indian.fold_4"
+indian-f5 = "mednet.classify.config.data.indian.fold_5"
+indian-f6 = "mednet.classify.config.data.indian.fold_6"
+indian-f7 = "mednet.classify.config.data.indian.fold_7"
+indian-f8 = "mednet.classify.config.data.indian.fold_8"
+indian-f9 = "mednet.classify.config.data.indian.fold_9"
# TBX11K dataset split 1: healthy vs active tb, and cross-validation folds
-tbx11k-v1-healthy-vs-atb = "mednet.libs.classification.config.data.tbx11k.v1_healthy_vs_atb"
-tbx11k-v1-f0 = "mednet.libs.classification.config.data.tbx11k.v1_fold_0"
-tbx11k-v1-f1 = "mednet.libs.classification.config.data.tbx11k.v1_fold_1"
-tbx11k-v1-f2 = "mednet.libs.classification.config.data.tbx11k.v1_fold_2"
-tbx11k-v1-f3 = "mednet.libs.classification.config.data.tbx11k.v1_fold_3"
-tbx11k-v1-f4 = "mednet.libs.classification.config.data.tbx11k.v1_fold_4"
-tbx11k-v1-f5 = "mednet.libs.classification.config.data.tbx11k.v1_fold_5"
-tbx11k-v1-f6 = "mednet.libs.classification.config.data.tbx11k.v1_fold_6"
-tbx11k-v1-f7 = "mednet.libs.classification.config.data.tbx11k.v1_fold_7"
-tbx11k-v1-f8 = "mednet.libs.classification.config.data.tbx11k.v1_fold_8"
-tbx11k-v1-f9 = "mednet.libs.classification.config.data.tbx11k.v1_fold_9"
+tbx11k-v1-healthy-vs-atb = "mednet.classify.config.data.tbx11k.v1_healthy_vs_atb"
+tbx11k-v1-f0 = "mednet.classify.config.data.tbx11k.v1_fold_0"
+tbx11k-v1-f1 = "mednet.classify.config.data.tbx11k.v1_fold_1"
+tbx11k-v1-f2 = "mednet.classify.config.data.tbx11k.v1_fold_2"
+tbx11k-v1-f3 = "mednet.classify.config.data.tbx11k.v1_fold_3"
+tbx11k-v1-f4 = "mednet.classify.config.data.tbx11k.v1_fold_4"
+tbx11k-v1-f5 = "mednet.classify.config.data.tbx11k.v1_fold_5"
+tbx11k-v1-f6 = "mednet.classify.config.data.tbx11k.v1_fold_6"
+tbx11k-v1-f7 = "mednet.classify.config.data.tbx11k.v1_fold_7"
+tbx11k-v1-f8 = "mednet.classify.config.data.tbx11k.v1_fold_8"
+tbx11k-v1-f9 = "mednet.classify.config.data.tbx11k.v1_fold_9"
# TBX11K dataset split 2: others vs active tb, and cross-validation folds
-tbx11k-v2-others-vs-atb = "mednet.libs.classification.config.data.tbx11k.v2_others_vs_atb"
-tbx11k-v2-f0 = "mednet.libs.classification.config.data.tbx11k.v2_fold_0"
-tbx11k-v2-f1 = "mednet.libs.classification.config.data.tbx11k.v2_fold_1"
-tbx11k-v2-f2 = "mednet.libs.classification.config.data.tbx11k.v2_fold_2"
-tbx11k-v2-f3 = "mednet.libs.classification.config.data.tbx11k.v2_fold_3"
-tbx11k-v2-f4 = "mednet.libs.classification.config.data.tbx11k.v2_fold_4"
-tbx11k-v2-f5 = "mednet.libs.classification.config.data.tbx11k.v2_fold_5"
-tbx11k-v2-f6 = "mednet.libs.classification.config.data.tbx11k.v2_fold_6"
-tbx11k-v2-f7 = "mednet.libs.classification.config.data.tbx11k.v2_fold_7"
-tbx11k-v2-f8 = "mednet.libs.classification.config.data.tbx11k.v2_fold_8"
-tbx11k-v2-f9 = "mednet.libs.classification.config.data.tbx11k.v2_fold_9"
+tbx11k-v2-others-vs-atb = "mednet.classify.config.data.tbx11k.v2_others_vs_atb"
+tbx11k-v2-f0 = "mednet.classify.config.data.tbx11k.v2_fold_0"
+tbx11k-v2-f1 = "mednet.classify.config.data.tbx11k.v2_fold_1"
+tbx11k-v2-f2 = "mednet.classify.config.data.tbx11k.v2_fold_2"
+tbx11k-v2-f3 = "mednet.classify.config.data.tbx11k.v2_fold_3"
+tbx11k-v2-f4 = "mednet.classify.config.data.tbx11k.v2_fold_4"
+tbx11k-v2-f5 = "mednet.classify.config.data.tbx11k.v2_fold_5"
+tbx11k-v2-f6 = "mednet.classify.config.data.tbx11k.v2_fold_6"
+tbx11k-v2-f7 = "mednet.classify.config.data.tbx11k.v2_fold_7"
+tbx11k-v2-f8 = "mednet.classify.config.data.tbx11k.v2_fold_8"
+tbx11k-v2-f9 = "mednet.classify.config.data.tbx11k.v2_fold_9"
# montgomery-shenzhen aggregated dataset
-montgomery-shenzhen = "mednet.libs.classification.config.data.montgomery_shenzhen.default"
-montgomery-shenzhen-f0 = "mednet.libs.classification.config.data.montgomery_shenzhen.fold_0"
-montgomery-shenzhen-f1 = "mednet.libs.classification.config.data.montgomery_shenzhen.fold_1"
-montgomery-shenzhen-f2 = "mednet.libs.classification.config.data.montgomery_shenzhen.fold_2"
-montgomery-shenzhen-f3 = "mednet.libs.classification.config.data.montgomery_shenzhen.fold_3"
-montgomery-shenzhen-f4 = "mednet.libs.classification.config.data.montgomery_shenzhen.fold_4"
-montgomery-shenzhen-f5 = "mednet.libs.classification.config.data.montgomery_shenzhen.fold_5"
-montgomery-shenzhen-f6 = "mednet.libs.classification.config.data.montgomery_shenzhen.fold_6"
-montgomery-shenzhen-f7 = "mednet.libs.classification.config.data.montgomery_shenzhen.fold_7"
-montgomery-shenzhen-f8 = "mednet.libs.classification.config.data.montgomery_shenzhen.fold_8"
-montgomery-shenzhen-f9 = "mednet.libs.classification.config.data.montgomery_shenzhen.fold_9"
+montgomery-shenzhen = "mednet.classify.config.data.montgomery_shenzhen.default"
+montgomery-shenzhen-f0 = "mednet.classify.config.data.montgomery_shenzhen.fold_0"
+montgomery-shenzhen-f1 = "mednet.classify.config.data.montgomery_shenzhen.fold_1"
+montgomery-shenzhen-f2 = "mednet.classify.config.data.montgomery_shenzhen.fold_2"
+montgomery-shenzhen-f3 = "mednet.classify.config.data.montgomery_shenzhen.fold_3"
+montgomery-shenzhen-f4 = "mednet.classify.config.data.montgomery_shenzhen.fold_4"
+montgomery-shenzhen-f5 = "mednet.classify.config.data.montgomery_shenzhen.fold_5"
+montgomery-shenzhen-f6 = "mednet.classify.config.data.montgomery_shenzhen.fold_6"
+montgomery-shenzhen-f7 = "mednet.classify.config.data.montgomery_shenzhen.fold_7"
+montgomery-shenzhen-f8 = "mednet.classify.config.data.montgomery_shenzhen.fold_8"
+montgomery-shenzhen-f9 = "mednet.classify.config.data.montgomery_shenzhen.fold_9"
# montgomery-shenzhen-indian aggregated dataset
-montgomery-shenzhen-indian = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.default"
-montgomery-shenzhen-indian-f0 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_0"
-montgomery-shenzhen-indian-f1 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_1"
-montgomery-shenzhen-indian-f2 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_2"
-montgomery-shenzhen-indian-f3 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_3"
-montgomery-shenzhen-indian-f4 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_4"
-montgomery-shenzhen-indian-f5 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_5"
-montgomery-shenzhen-indian-f6 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_6"
-montgomery-shenzhen-indian-f7 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_7"
-montgomery-shenzhen-indian-f8 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_8"
-montgomery-shenzhen-indian-f9 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian.fold_9"
+montgomery-shenzhen-indian = "mednet.classify.config.data.montgomery_shenzhen_indian.default"
+montgomery-shenzhen-indian-f0 = "mednet.classify.config.data.montgomery_shenzhen_indian.fold_0"
+montgomery-shenzhen-indian-f1 = "mednet.classify.config.data.montgomery_shenzhen_indian.fold_1"
+montgomery-shenzhen-indian-f2 = "mednet.classify.config.data.montgomery_shenzhen_indian.fold_2"
+montgomery-shenzhen-indian-f3 = "mednet.classify.config.data.montgomery_shenzhen_indian.fold_3"
+montgomery-shenzhen-indian-f4 = "mednet.classify.config.data.montgomery_shenzhen_indian.fold_4"
+montgomery-shenzhen-indian-f5 = "mednet.classify.config.data.montgomery_shenzhen_indian.fold_5"
+montgomery-shenzhen-indian-f6 = "mednet.classify.config.data.montgomery_shenzhen_indian.fold_6"
+montgomery-shenzhen-indian-f7 = "mednet.classify.config.data.montgomery_shenzhen_indian.fold_7"
+montgomery-shenzhen-indian-f8 = "mednet.classify.config.data.montgomery_shenzhen_indian.fold_8"
+montgomery-shenzhen-indian-f9 = "mednet.classify.config.data.montgomery_shenzhen_indian.fold_9"
# montgomery-shenzhen-indian-tbx11k aggregated dataset
-montgomery-shenzhen-indian-tbx11k-v1 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_healthy_vs_atb"
-montgomery-shenzhen-indian-tbx11k-v1-f0 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_0"
-montgomery-shenzhen-indian-tbx11k-v1-f1 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_1"
-montgomery-shenzhen-indian-tbx11k-v1-f2 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_2"
-montgomery-shenzhen-indian-tbx11k-v1-f3 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_3"
-montgomery-shenzhen-indian-tbx11k-v1-f4 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_4"
-montgomery-shenzhen-indian-tbx11k-v1-f5 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_5"
-montgomery-shenzhen-indian-tbx11k-v1-f6 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_6"
-montgomery-shenzhen-indian-tbx11k-v1-f7 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_7"
-montgomery-shenzhen-indian-tbx11k-v1-f8 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_8"
-montgomery-shenzhen-indian-tbx11k-v1-f9 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_9"
-montgomery-shenzhen-indian-tbx11k-v2 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_others_vs_atb"
-montgomery-shenzhen-indian-tbx11k-v2-f0 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_0"
-montgomery-shenzhen-indian-tbx11k-v2-f1 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_1"
-montgomery-shenzhen-indian-tbx11k-v2-f2 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_2"
-montgomery-shenzhen-indian-tbx11k-v2-f3 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_3"
-montgomery-shenzhen-indian-tbx11k-v2-f4 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_4"
-montgomery-shenzhen-indian-tbx11k-v2-f5 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_5"
-montgomery-shenzhen-indian-tbx11k-v2-f6 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_6"
-montgomery-shenzhen-indian-tbx11k-v2-f7 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_7"
-montgomery-shenzhen-indian-tbx11k-v2-f8 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_8"
-montgomery-shenzhen-indian-tbx11k-v2-f9 = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_9"
+montgomery-shenzhen-indian-tbx11k-v1 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_healthy_vs_atb"
+montgomery-shenzhen-indian-tbx11k-v1-f0 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_0"
+montgomery-shenzhen-indian-tbx11k-v1-f1 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_1"
+montgomery-shenzhen-indian-tbx11k-v1-f2 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_2"
+montgomery-shenzhen-indian-tbx11k-v1-f3 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_3"
+montgomery-shenzhen-indian-tbx11k-v1-f4 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_4"
+montgomery-shenzhen-indian-tbx11k-v1-f5 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_5"
+montgomery-shenzhen-indian-tbx11k-v1-f6 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_6"
+montgomery-shenzhen-indian-tbx11k-v1-f7 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_7"
+montgomery-shenzhen-indian-tbx11k-v1-f8 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_8"
+montgomery-shenzhen-indian-tbx11k-v1-f9 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v1_fold_9"
+montgomery-shenzhen-indian-tbx11k-v2 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_others_vs_atb"
+montgomery-shenzhen-indian-tbx11k-v2-f0 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_0"
+montgomery-shenzhen-indian-tbx11k-v2-f1 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_1"
+montgomery-shenzhen-indian-tbx11k-v2-f2 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_2"
+montgomery-shenzhen-indian-tbx11k-v2-f3 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_3"
+montgomery-shenzhen-indian-tbx11k-v2-f4 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_4"
+montgomery-shenzhen-indian-tbx11k-v2-f5 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_5"
+montgomery-shenzhen-indian-tbx11k-v2-f6 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_6"
+montgomery-shenzhen-indian-tbx11k-v2-f7 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_7"
+montgomery-shenzhen-indian-tbx11k-v2-f8 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_8"
+montgomery-shenzhen-indian-tbx11k-v2-f9 = "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.v2_fold_9"
# tbpoc dataset (only cross-validation folds)
-tbpoc-f0 = "mednet.libs.classification.config.data.tbpoc.fold_0"
-tbpoc-f1 = "mednet.libs.classification.config.data.tbpoc.fold_1"
-tbpoc-f2 = "mednet.libs.classification.config.data.tbpoc.fold_2"
-tbpoc-f3 = "mednet.libs.classification.config.data.tbpoc.fold_3"
-tbpoc-f4 = "mednet.libs.classification.config.data.tbpoc.fold_4"
-tbpoc-f5 = "mednet.libs.classification.config.data.tbpoc.fold_5"
-tbpoc-f6 = "mednet.libs.classification.config.data.tbpoc.fold_6"
-tbpoc-f7 = "mednet.libs.classification.config.data.tbpoc.fold_7"
-tbpoc-f8 = "mednet.libs.classification.config.data.tbpoc.fold_8"
-tbpoc-f9 = "mednet.libs.classification.config.data.tbpoc.fold_9"
+tbpoc-f0 = "mednet.classify.config.data.tbpoc.fold_0"
+tbpoc-f1 = "mednet.classify.config.data.tbpoc.fold_1"
+tbpoc-f2 = "mednet.classify.config.data.tbpoc.fold_2"
+tbpoc-f3 = "mednet.classify.config.data.tbpoc.fold_3"
+tbpoc-f4 = "mednet.classify.config.data.tbpoc.fold_4"
+tbpoc-f5 = "mednet.classify.config.data.tbpoc.fold_5"
+tbpoc-f6 = "mednet.classify.config.data.tbpoc.fold_6"
+tbpoc-f7 = "mednet.classify.config.data.tbpoc.fold_7"
+tbpoc-f8 = "mednet.classify.config.data.tbpoc.fold_8"
+tbpoc-f9 = "mednet.classify.config.data.tbpoc.fold_9"
# hivtb dataset (only cross-validation folds)
-hivtb-f0 = "mednet.libs.classification.config.data.hivtb.fold_0"
-hivtb-f1 = "mednet.libs.classification.config.data.hivtb.fold_1"
-hivtb-f2 = "mednet.libs.classification.config.data.hivtb.fold_2"
-hivtb-f3 = "mednet.libs.classification.config.data.hivtb.fold_3"
-hivtb-f4 = "mednet.libs.classification.config.data.hivtb.fold_4"
-hivtb-f5 = "mednet.libs.classification.config.data.hivtb.fold_5"
-hivtb-f6 = "mednet.libs.classification.config.data.hivtb.fold_6"
-hivtb-f7 = "mednet.libs.classification.config.data.hivtb.fold_7"
-hivtb-f8 = "mednet.libs.classification.config.data.hivtb.fold_8"
-hivtb-f9 = "mednet.libs.classification.config.data.hivtb.fold_9"
+hivtb-f0 = "mednet.classify.config.data.hivtb.fold_0"
+hivtb-f1 = "mednet.classify.config.data.hivtb.fold_1"
+hivtb-f2 = "mednet.classify.config.data.hivtb.fold_2"
+hivtb-f3 = "mednet.classify.config.data.hivtb.fold_3"
+hivtb-f4 = "mednet.classify.config.data.hivtb.fold_4"
+hivtb-f5 = "mednet.classify.config.data.hivtb.fold_5"
+hivtb-f6 = "mednet.classify.config.data.hivtb.fold_6"
+hivtb-f7 = "mednet.classify.config.data.hivtb.fold_7"
+hivtb-f8 = "mednet.classify.config.data.hivtb.fold_8"
+hivtb-f9 = "mednet.classify.config.data.hivtb.fold_9"
# NIH CXR14 (relabeled), multi-class (14 labels)
-nih-cxr14 = "mednet.libs.classification.config.data.nih_cxr14.default"
-nih-cxr14-cardiomegaly = "mednet.libs.classification.config.data.nih_cxr14.cardiomegaly"
+nih-cxr14 = "mednet.classify.config.data.nih_cxr14.default"
+nih-cxr14-cardiomegaly = "mednet.classify.config.data.nih_cxr14.cardiomegaly"
# PadChest, multi-class (varied number of labels)
-padchest-idiap = "mednet.libs.classification.config.data.padchest.idiap"
-padchest-tb-idiap = "mednet.libs.classification.config.data.padchest.tb_idiap"
-padchest-no-tb-idiap = "mednet.libs.classification.config.data.padchest.no_tb_idiap"
-padchest-cardiomegaly-idiap = "mednet.libs.classification.config.data.padchest.cardiomegaly_idiap"
+padchest-idiap = "mednet.classify.config.data.padchest.idiap"
+padchest-tb-idiap = "mednet.classify.config.data.padchest.tb_idiap"
+padchest-no-tb-idiap = "mednet.classify.config.data.padchest.no_tb_idiap"
+padchest-cardiomegaly-idiap = "mednet.classify.config.data.padchest.cardiomegaly_idiap"
# NIH CXR14 / PadChest aggregated dataset
-nih-cxr14-padchest = "mednet.libs.classification.config.data.nih_cxr14_padchest.idiap"
+nih-cxr14-padchest = "mednet.classify.config.data.nih_cxr14_padchest.idiap"
# montgomery-shenzhen-indian-padchest aggregated dataset
-montgomery-shenzhen-indian-padchest = "mednet.libs.classification.config.data.montgomery_shenzhen_indian_padchest.default"
+montgomery-shenzhen-indian-padchest = "mednet.classify.config.data.montgomery_shenzhen_indian_padchest.default"
# VISCERAL dataset
-visceral = "mednet.libs.classification.config.data.visceral.default"
-
-[project.entry-points."mednet.libs.segmentation.config"]
-
-# models
-driu = "mednet.libs.segmentation.config.models.driu"
-driu-bn = "mednet.libs.segmentation.config.models.driu_bn"
-driu-od = "mednet.libs.segmentation.config.models.driu_od"
-driu-pix = "mednet.libs.segmentation.config.models.driu_pix"
-hed = "mednet.libs.segmentation.config.models.hed"
-lwnet = "mednet.libs.segmentation.config.models.lwnet"
-m2unet = "mednet.libs.segmentation.config.models.m2unet"
-unet = "mednet.libs.segmentation.config.models.unet"
-
-affine = "mednet.libs.common.config.augmentations.affine"
-elastic = "mednet.libs.common.config.augmentations.elastic"
-hflip = "mednet.libs.common.config.augmentations.hflip"
-jitter = "mednet.libs.common.config.augmentations.jitter"
-hflip-affine = "mednet.libs.common.config.augmentations.hflip_affine"
-hflip-jitter-affine = "mednet.libs.common.config.augmentations.hflip_jitter_affine"
+visceral = "mednet.classify.config.data.visceral.default"
# chase-db1 - retinography
-chasedb1 = "mednet.libs.segmentation.config.data.chasedb1.first_annotator"
-chasedb1-2nd = "mednet.libs.segmentation.config.data.chasedb1.second_annotator"
+chasedb1 = "mednet.segment.config.data.chasedb1.first_annotator"
+chasedb1-2nd = "mednet.segment.config.data.chasedb1.second_annotator"
# cxr8 - cxr
-cxr8 = "mednet.libs.segmentation.config.data.cxr8.default"
+cxr8 = "mednet.segment.config.data.cxr8.default"
# drhagis dataset - retinography
-drhagis = "mednet.libs.segmentation.config.data.drhagis.default"
+drhagis = "mednet.segment.config.data.drhagis.default"
# drionsdb - retinography
-drionsdb = "mednet.libs.segmentation.config.data.drionsdb.expert1"
-drionsdb-2nd = "mednet.libs.segmentation.config.data.drionsdb.expert2"
+drionsdb = "mednet.segment.config.data.drionsdb.expert1"
+drionsdb-2nd = "mednet.segment.config.data.drionsdb.expert2"
# drive dataset - retinography
-drive = "mednet.libs.segmentation.config.data.drive.default"
-drive-2nd = "mednet.libs.segmentation.config.data.drive.drive_2nd"
+drive = "mednet.segment.config.data.drive.default"
+drive-2nd = "mednet.segment.config.data.drive.drive_2nd"
# drishti-gs1 - retinography
-drishtigs1-disc-all = "mednet.libs.segmentation.config.data.drishtigs1.optic_disc_all"
-drishtigs1-disc-any = "mednet.libs.segmentation.config.data.drishtigs1.optic_disc_any"
-drishtigs1-cup-all = "mednet.libs.segmentation.config.data.drishtigs1.optic_cup_all"
-drishtigs1-cup-any = "mednet.libs.segmentation.config.data.drishtigs1.optic_cup_any"
+drishtigs1-disc-all = "mednet.segment.config.data.drishtigs1.optic_disc_all"
+drishtigs1-disc-any = "mednet.segment.config.data.drishtigs1.optic_disc_any"
+drishtigs1-cup-all = "mednet.segment.config.data.drishtigs1.optic_cup_all"
+drishtigs1-cup-any = "mednet.segment.config.data.drishtigs1.optic_cup_any"
# hrf - retinography
-hrf = "mednet.libs.segmentation.config.data.hrf.default"
+hrf = "mednet.segment.config.data.hrf.default"
# iostar - retinography
-iostar-vessel = "mednet.libs.segmentation.config.data.iostar.vessel"
-iostar-disc = "mednet.libs.segmentation.config.data.iostar.optic_disc"
+iostar-vessel = "mednet.segment.config.data.iostar.vessel"
+iostar-disc = "mednet.segment.config.data.iostar.optic_disc"
# jsrt - cxr
-jsrt = "mednet.libs.segmentation.config.data.jsrt.default"
+jsrt = "mednet.segment.config.data.jsrt.default"
# montgomery county - cxr
-montgomery = "mednet.libs.segmentation.config.data.montgomery.default"
+montgomery-segment = "mednet.segment.config.data.montgomery.default"
# refuge - retinography
-refuge-cup = "mednet.libs.segmentation.config.data.refuge.cup"
-refuge-disc = "mednet.libs.segmentation.config.data.refuge.disc"
+refuge-cup = "mednet.segment.config.data.refuge.cup"
+refuge-disc = "mednet.segment.config.data.refuge.disc"
# rim one r3 - retinography
-rimoner3-cup = "mednet.libs.segmentation.config.data.rimoner3.cup_exp1"
-rimoner3-disc = "mednet.libs.segmentation.config.data.rimoner3.disc_exp1"
-rimoner3-cup-2nd = "mednet.libs.segmentation.config.data.rimoner3.cup_exp2"
-rimoner3-disc-2nd = "mednet.libs.segmentation.config.data.rimoner3.disc_exp2"
+rimoner3-cup = "mednet.segment.config.data.rimoner3.cup_exp1"
+rimoner3-disc = "mednet.segment.config.data.rimoner3.disc_exp1"
+rimoner3-cup-2nd = "mednet.segment.config.data.rimoner3.cup_exp2"
+rimoner3-disc-2nd = "mednet.segment.config.data.rimoner3.disc_exp2"
# shenzhen - cxr
-shenzhen = "mednet.libs.segmentation.config.data.shenzhen.default"
+shenzhen-segment = "mednet.segment.config.data.shenzhen.default"
# stare dataset - retinography
-stare = "mednet.libs.segmentation.config.data.stare.ah"
-stare-2nd = "mednet.libs.segmentation.config.data.stare.vk"
+stare = "mednet.segment.config.data.stare.ah"
+stare-2nd = "mednet.segment.config.data.stare.vk"
[tool.ruff]
line-length = 88
diff --git a/src/mednet/libs/classification/__init__.py b/src/mednet/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/__init__.py
rename to src/mednet/__init__.py
diff --git a/src/mednet/libs/classification/config/__init__.py b/src/mednet/classify/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/__init__.py
rename to src/mednet/classify/__init__.py
diff --git a/src/mednet/libs/classification/config/data/__init__.py b/src/mednet/classify/config/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/__init__.py
rename to src/mednet/classify/config/__init__.py
diff --git a/src/mednet/libs/classification/config/data/hivtb/__init__.py b/src/mednet/classify/config/data/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/__init__.py
rename to src/mednet/classify/config/data/__init__.py
diff --git a/src/mednet/libs/classification/config/data/indian/__init__.py b/src/mednet/classify/config/data/hivtb/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/__init__.py
rename to src/mednet/classify/config/data/hivtb/__init__.py
diff --git a/src/mednet/libs/classification/config/data/hivtb/datamodule.py b/src/mednet/classify/config/data/hivtb/datamodule.py
similarity index 86%
rename from src/mednet/libs/classification/config/data/hivtb/datamodule.py
rename to src/mednet/classify/config/data/hivtb/datamodule.py
index cebf4036..354a40f8 100644
--- a/src/mednet/libs/classification/config/data/hivtb/datamodule.py
+++ b/src/mednet/classify/config/data/hivtb/datamodule.py
@@ -8,18 +8,18 @@ Database reference: [HIV-TB-2019]_
import os
import pathlib
+import typing
import PIL.Image
-from mednet.libs.classification.data.typing import (
- ClassificationRawDataLoader as _ClassificationRawDataLoader,
-)
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.image_utils import remove_black_borders
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.data.typing import Sample
-from mednet.libs.common.utils.rc import load_rc
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.image_utils import remove_black_borders
+from .....data.split import make_split
+from .....data.typing import Sample
+from .....utils.rc import load_rc
+from ....data.typing import ClassificationRawDataLoader as _ClassificationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -40,7 +40,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
),
)
- def sample(self, sample: tuple[str, int]) -> Sample:
+ def sample(self, sample: tuple[str, int, typing.Any | None]) -> Sample:
"""Load a single image sample from the disk.
Parameters
@@ -66,12 +66,12 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
return tensor, dict(target=sample[1], name=sample[0]) # type: ignore[arg-type]
- def target(self, sample: tuple[str, int]) -> int:
+ def target(self, k: typing.Any) -> int | list[int]:
"""Load a single image sample target from the disk.
Parameters
----------
- sample
+ k
A tuple containing the path suffix, within the dataset root folder,
where to find the image to be loaded, and an integer, representing
the sample target.
@@ -82,7 +82,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
The integer target associated with the sample.
"""
- return sample[1]
+ return k[1]
class DataModule(CachingDataModule):
@@ -127,4 +127,5 @@ class DataModule(CachingDataModule):
raw_data_loader=ClassificationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold-0.json b/src/mednet/classify/config/data/hivtb/fold-0.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/fold-0.json
rename to src/mednet/classify/config/data/hivtb/fold-0.json
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold-1.json b/src/mednet/classify/config/data/hivtb/fold-1.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/fold-1.json
rename to src/mednet/classify/config/data/hivtb/fold-1.json
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold-2.json b/src/mednet/classify/config/data/hivtb/fold-2.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/fold-2.json
rename to src/mednet/classify/config/data/hivtb/fold-2.json
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold-3.json b/src/mednet/classify/config/data/hivtb/fold-3.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/fold-3.json
rename to src/mednet/classify/config/data/hivtb/fold-3.json
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold-4.json b/src/mednet/classify/config/data/hivtb/fold-4.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/fold-4.json
rename to src/mednet/classify/config/data/hivtb/fold-4.json
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold-5.json b/src/mednet/classify/config/data/hivtb/fold-5.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/fold-5.json
rename to src/mednet/classify/config/data/hivtb/fold-5.json
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold-6.json b/src/mednet/classify/config/data/hivtb/fold-6.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/fold-6.json
rename to src/mednet/classify/config/data/hivtb/fold-6.json
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold-7.json b/src/mednet/classify/config/data/hivtb/fold-7.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/fold-7.json
rename to src/mednet/classify/config/data/hivtb/fold-7.json
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold-8.json b/src/mednet/classify/config/data/hivtb/fold-8.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/fold-8.json
rename to src/mednet/classify/config/data/hivtb/fold-8.json
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold-9.json b/src/mednet/classify/config/data/hivtb/fold-9.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/hivtb/fold-9.json
rename to src/mednet/classify/config/data/hivtb/fold-9.json
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold_0.py b/src/mednet/classify/config/data/hivtb/fold_0.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/hivtb/fold_0.py
rename to src/mednet/classify/config/data/hivtb/fold_0.py
index 1c64db6d..17dd6120 100644
--- a/src/mednet/libs/classification/config/data/hivtb/fold_0.py
+++ b/src/mednet/classify/config/data/hivtb/fold_0.py
@@ -5,9 +5,10 @@
Database reference: [HIV-TB-2019]_
-See :py:class:`mednet.libs.classification.config.data.hivtb.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.hivtb.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.hivtb.datamodule import DataModule
+from mednet.classify.config.data.hivtb.datamodule import DataModule
datamodule = DataModule("fold-0.json")
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold_1.py b/src/mednet/classify/config/data/hivtb/fold_1.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/hivtb/fold_1.py
rename to src/mednet/classify/config/data/hivtb/fold_1.py
index 98401e1e..00df532a 100644
--- a/src/mednet/libs/classification/config/data/hivtb/fold_1.py
+++ b/src/mednet/classify/config/data/hivtb/fold_1.py
@@ -5,9 +5,10 @@
Database reference: [HIV-TB-2019]_
-See :py:class:`mednet.libs.classification.config.data.hivtb.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.hivtb.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.hivtb.datamodule import DataModule
+from mednet.classify.config.data.hivtb.datamodule import DataModule
datamodule = DataModule("fold-1.json")
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold_2.py b/src/mednet/classify/config/data/hivtb/fold_2.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/hivtb/fold_2.py
rename to src/mednet/classify/config/data/hivtb/fold_2.py
index b977dee9..77601f06 100644
--- a/src/mednet/libs/classification/config/data/hivtb/fold_2.py
+++ b/src/mednet/classify/config/data/hivtb/fold_2.py
@@ -5,9 +5,10 @@
Database reference: [HIV-TB-2019]_
-See :py:class:`mednet.libs.classification.config.data.hivtb.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.hivtb.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.hivtb.datamodule import DataModule
+from mednet.classify.config.data.hivtb.datamodule import DataModule
datamodule = DataModule("fold-2.json")
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold_3.py b/src/mednet/classify/config/data/hivtb/fold_3.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/hivtb/fold_3.py
rename to src/mednet/classify/config/data/hivtb/fold_3.py
index e3ab0791..410e981a 100644
--- a/src/mednet/libs/classification/config/data/hivtb/fold_3.py
+++ b/src/mednet/classify/config/data/hivtb/fold_3.py
@@ -5,9 +5,10 @@
Database reference: [HIV-TB-2019]_
-See :py:class:`mednet.libs.classification.config.data.hivtb.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.hivtb.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.hivtb.datamodule import DataModule
+from mednet.classify.config.data.hivtb.datamodule import DataModule
datamodule = DataModule("fold-3.json")
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold_4.py b/src/mednet/classify/config/data/hivtb/fold_4.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/hivtb/fold_4.py
rename to src/mednet/classify/config/data/hivtb/fold_4.py
index 72ce7243..8272960e 100644
--- a/src/mednet/libs/classification/config/data/hivtb/fold_4.py
+++ b/src/mednet/classify/config/data/hivtb/fold_4.py
@@ -5,9 +5,10 @@
Database reference: [HIV-TB-2019]_
-See :py:class:`mednet.libs.classification.config.data.hivtb.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.hivtb.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.hivtb.datamodule import DataModule
+from mednet.classify.config.data.hivtb.datamodule import DataModule
datamodule = DataModule("fold-4.json")
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold_5.py b/src/mednet/classify/config/data/hivtb/fold_5.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/hivtb/fold_5.py
rename to src/mednet/classify/config/data/hivtb/fold_5.py
index 18ab3a98..34eab9b1 100644
--- a/src/mednet/libs/classification/config/data/hivtb/fold_5.py
+++ b/src/mednet/classify/config/data/hivtb/fold_5.py
@@ -5,9 +5,10 @@
Database reference: [HIV-TB-2019]_
-See :py:class:`mednet.libs.classification.config.data.hivtb.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.hivtb.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.hivtb.datamodule import DataModule
+from mednet.classify.config.data.hivtb.datamodule import DataModule
datamodule = DataModule("fold-5.json")
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold_6.py b/src/mednet/classify/config/data/hivtb/fold_6.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/hivtb/fold_6.py
rename to src/mednet/classify/config/data/hivtb/fold_6.py
index 0763f92e..dfd71f8b 100644
--- a/src/mednet/libs/classification/config/data/hivtb/fold_6.py
+++ b/src/mednet/classify/config/data/hivtb/fold_6.py
@@ -5,9 +5,10 @@
Database reference: [HIV-TB-2019]_
-See :py:class:`mednet.libs.classification.config.data.hivtb.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.hivtb.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.hivtb.datamodule import DataModule
+from mednet.classify.config.data.hivtb.datamodule import DataModule
datamodule = DataModule("fold-6.json")
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold_7.py b/src/mednet/classify/config/data/hivtb/fold_7.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/hivtb/fold_7.py
rename to src/mednet/classify/config/data/hivtb/fold_7.py
index 4078ef8a..323e5f22 100644
--- a/src/mednet/libs/classification/config/data/hivtb/fold_7.py
+++ b/src/mednet/classify/config/data/hivtb/fold_7.py
@@ -5,9 +5,10 @@
Database reference: [HIV-TB-2019]_
-See :py:class:`mednet.libs.classification.config.data.hivtb.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.hivtb.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.hivtb.datamodule import DataModule
+from mednet.classify.config.data.hivtb.datamodule import DataModule
datamodule = DataModule("fold-7.json")
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold_8.py b/src/mednet/classify/config/data/hivtb/fold_8.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/hivtb/fold_8.py
rename to src/mednet/classify/config/data/hivtb/fold_8.py
index 8f26c539..f599bc1c 100644
--- a/src/mednet/libs/classification/config/data/hivtb/fold_8.py
+++ b/src/mednet/classify/config/data/hivtb/fold_8.py
@@ -5,9 +5,10 @@
Database reference: [HIV-TB-2019]_
-See :py:class:`mednet.libs.classification.config.data.hivtb.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.hivtb.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.hivtb.datamodule import DataModule
+from mednet.classify.config.data.hivtb.datamodule import DataModule
datamodule = DataModule("fold-8.json")
diff --git a/src/mednet/libs/classification/config/data/hivtb/fold_9.py b/src/mednet/classify/config/data/hivtb/fold_9.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/hivtb/fold_9.py
rename to src/mednet/classify/config/data/hivtb/fold_9.py
index 911590af..5e73424c 100644
--- a/src/mednet/libs/classification/config/data/hivtb/fold_9.py
+++ b/src/mednet/classify/config/data/hivtb/fold_9.py
@@ -5,9 +5,10 @@
Database reference: [HIV-TB-2019]_
-See :py:class:`mednet.libs.classification.config.data.hivtb.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.hivtb.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.hivtb.datamodule import DataModule
+from mednet.classify.config.data.hivtb.datamodule import DataModule
datamodule = DataModule("fold-9.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/__init__.py b/src/mednet/classify/config/data/indian/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/__init__.py
rename to src/mednet/classify/config/data/indian/__init__.py
diff --git a/src/mednet/libs/classification/config/data/indian/datamodule.py b/src/mednet/classify/config/data/indian/datamodule.py
similarity index 91%
rename from src/mednet/libs/classification/config/data/indian/datamodule.py
rename to src/mednet/classify/config/data/indian/datamodule.py
index efcce8e7..f888f054 100644
--- a/src/mednet/libs/classification/config/data/indian/datamodule.py
+++ b/src/mednet/classify/config/data/indian/datamodule.py
@@ -8,10 +8,9 @@ Database reference: [INDIAN-2013]_
import pathlib
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-
-from ....config.data.shenzhen.datamodule import ClassificationRawDataLoader
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from ..shenzhen.datamodule import ClassificationRawDataLoader
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
@@ -68,4 +67,5 @@ class DataModule(CachingDataModule):
),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/indian/default.json b/src/mednet/classify/config/data/indian/default.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/default.json
rename to src/mednet/classify/config/data/indian/default.json
diff --git a/src/mednet/libs/classification/config/data/indian/default.py b/src/mednet/classify/config/data/indian/default.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/indian/default.py
rename to src/mednet/classify/config/data/indian/default.py
index 4633effd..d842735e 100644
--- a/src/mednet/libs/classification/config/data/indian/default.py
+++ b/src/mednet/classify/config/data/indian/default.py
@@ -5,9 +5,9 @@
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/classification/config/data/indian/fold-0.json b/src/mednet/classify/config/data/indian/fold-0.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/fold-0.json
rename to src/mednet/classify/config/data/indian/fold-0.json
diff --git a/src/mednet/libs/classification/config/data/indian/fold-1.json b/src/mednet/classify/config/data/indian/fold-1.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/fold-1.json
rename to src/mednet/classify/config/data/indian/fold-1.json
diff --git a/src/mednet/libs/classification/config/data/indian/fold-2.json b/src/mednet/classify/config/data/indian/fold-2.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/fold-2.json
rename to src/mednet/classify/config/data/indian/fold-2.json
diff --git a/src/mednet/libs/classification/config/data/indian/fold-3.json b/src/mednet/classify/config/data/indian/fold-3.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/fold-3.json
rename to src/mednet/classify/config/data/indian/fold-3.json
diff --git a/src/mednet/libs/classification/config/data/indian/fold-4.json b/src/mednet/classify/config/data/indian/fold-4.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/fold-4.json
rename to src/mednet/classify/config/data/indian/fold-4.json
diff --git a/src/mednet/libs/classification/config/data/indian/fold-5.json b/src/mednet/classify/config/data/indian/fold-5.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/fold-5.json
rename to src/mednet/classify/config/data/indian/fold-5.json
diff --git a/src/mednet/libs/classification/config/data/indian/fold-6.json b/src/mednet/classify/config/data/indian/fold-6.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/fold-6.json
rename to src/mednet/classify/config/data/indian/fold-6.json
diff --git a/src/mednet/libs/classification/config/data/indian/fold-7.json b/src/mednet/classify/config/data/indian/fold-7.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/fold-7.json
rename to src/mednet/classify/config/data/indian/fold-7.json
diff --git a/src/mednet/libs/classification/config/data/indian/fold-8.json b/src/mednet/classify/config/data/indian/fold-8.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/fold-8.json
rename to src/mednet/classify/config/data/indian/fold-8.json
diff --git a/src/mednet/libs/classification/config/data/indian/fold-9.json b/src/mednet/classify/config/data/indian/fold-9.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/indian/fold-9.json
rename to src/mednet/classify/config/data/indian/fold-9.json
diff --git a/src/mednet/libs/classification/config/data/indian/fold_0.py b/src/mednet/classify/config/data/indian/fold_0.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/indian/fold_0.py
rename to src/mednet/classify/config/data/indian/fold_0.py
index b476423f..e66d9304 100644
--- a/src/mednet/libs/classification/config/data/indian/fold_0.py
+++ b/src/mednet/classify/config/data/indian/fold_0.py
@@ -6,9 +6,10 @@
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("fold-0.json")
diff --git a/src/mednet/libs/classification/config/data/indian/fold_1.py b/src/mednet/classify/config/data/indian/fold_1.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/indian/fold_1.py
rename to src/mednet/classify/config/data/indian/fold_1.py
index 52560934..7c7bb300 100644
--- a/src/mednet/libs/classification/config/data/indian/fold_1.py
+++ b/src/mednet/classify/config/data/indian/fold_1.py
@@ -6,9 +6,10 @@ fold 1).
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("fold-1.json")
diff --git a/src/mednet/libs/classification/config/data/indian/fold_2.py b/src/mednet/classify/config/data/indian/fold_2.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/indian/fold_2.py
rename to src/mednet/classify/config/data/indian/fold_2.py
index f9857d82..1afad5c6 100644
--- a/src/mednet/libs/classification/config/data/indian/fold_2.py
+++ b/src/mednet/classify/config/data/indian/fold_2.py
@@ -6,9 +6,10 @@ fold 2).
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("fold-2.json")
diff --git a/src/mednet/libs/classification/config/data/indian/fold_3.py b/src/mednet/classify/config/data/indian/fold_3.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/indian/fold_3.py
rename to src/mednet/classify/config/data/indian/fold_3.py
index fc3ca3aa..a0be8bd8 100644
--- a/src/mednet/libs/classification/config/data/indian/fold_3.py
+++ b/src/mednet/classify/config/data/indian/fold_3.py
@@ -6,9 +6,10 @@ fold 3).
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("fold-3.json")
diff --git a/src/mednet/libs/classification/config/data/indian/fold_4.py b/src/mednet/classify/config/data/indian/fold_4.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/indian/fold_4.py
rename to src/mednet/classify/config/data/indian/fold_4.py
index b42e140c..7a5314ce 100644
--- a/src/mednet/libs/classification/config/data/indian/fold_4.py
+++ b/src/mednet/classify/config/data/indian/fold_4.py
@@ -6,9 +6,10 @@ fold 4).
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("fold-4.json")
diff --git a/src/mednet/libs/classification/config/data/indian/fold_5.py b/src/mednet/classify/config/data/indian/fold_5.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/indian/fold_5.py
rename to src/mednet/classify/config/data/indian/fold_5.py
index c2bbc56a..623de9da 100644
--- a/src/mednet/libs/classification/config/data/indian/fold_5.py
+++ b/src/mednet/classify/config/data/indian/fold_5.py
@@ -6,9 +6,10 @@ fold 5).
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("fold-5.json")
diff --git a/src/mednet/libs/classification/config/data/indian/fold_6.py b/src/mednet/classify/config/data/indian/fold_6.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/indian/fold_6.py
rename to src/mednet/classify/config/data/indian/fold_6.py
index 9bb255b6..35500c61 100644
--- a/src/mednet/libs/classification/config/data/indian/fold_6.py
+++ b/src/mednet/classify/config/data/indian/fold_6.py
@@ -6,9 +6,10 @@ fold 6).
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("fold-6.json")
diff --git a/src/mednet/libs/classification/config/data/indian/fold_7.py b/src/mednet/classify/config/data/indian/fold_7.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/indian/fold_7.py
rename to src/mednet/classify/config/data/indian/fold_7.py
index 35cd3477..8c41ced0 100644
--- a/src/mednet/libs/classification/config/data/indian/fold_7.py
+++ b/src/mednet/classify/config/data/indian/fold_7.py
@@ -6,9 +6,10 @@ fold 7).
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("fold-7.json")
diff --git a/src/mednet/libs/classification/config/data/indian/fold_8.py b/src/mednet/classify/config/data/indian/fold_8.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/indian/fold_8.py
rename to src/mednet/classify/config/data/indian/fold_8.py
index df089e03..3eb789c0 100644
--- a/src/mednet/libs/classification/config/data/indian/fold_8.py
+++ b/src/mednet/classify/config/data/indian/fold_8.py
@@ -6,9 +6,10 @@ fold 8).
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("fold-8.json")
diff --git a/src/mednet/libs/classification/config/data/indian/fold_9.py b/src/mednet/classify/config/data/indian/fold_9.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/indian/fold_9.py
rename to src/mednet/classify/config/data/indian/fold_9.py
index b0d0d5ab..071912cd 100644
--- a/src/mednet/libs/classification/config/data/indian/fold_9.py
+++ b/src/mednet/classify/config/data/indian/fold_9.py
@@ -6,9 +6,10 @@ fold 9).
Database reference: [INDIAN-2013]_
-See :py:class:`mednet.libs.classification.config.data.indian.datamodule.DataModule` for technical details.
+See :py:class:`mednet.classify.config.data.indian.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.indian.datamodule import DataModule
+from mednet.classify.config.data.indian.datamodule import DataModule
datamodule = DataModule("fold-9.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/__init__.py b/src/mednet/classify/config/data/montgomery/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/__init__.py
rename to src/mednet/classify/config/data/montgomery/__init__.py
diff --git a/src/mednet/libs/classification/config/data/montgomery/datamodule.py b/src/mednet/classify/config/data/montgomery/datamodule.py
similarity index 87%
rename from src/mednet/libs/classification/config/data/montgomery/datamodule.py
rename to src/mednet/classify/config/data/montgomery/datamodule.py
index 52f23320..6b5aeaa2 100644
--- a/src/mednet/libs/classification/config/data/montgomery/datamodule.py
+++ b/src/mednet/classify/config/data/montgomery/datamodule.py
@@ -8,18 +8,18 @@ Database reference: [MONTGOMERY-SHENZHEN-2014]_
import os
import pathlib
+import typing
import PIL.Image
-from mednet.libs.classification.data.typing import (
- ClassificationRawDataLoader as _ClassificationRawDataLoader,
-)
-from mednet.libs.classification.data.typing import Sample
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.image_utils import remove_black_borders
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.image_utils import remove_black_borders
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import ClassificationRawDataLoader as _ClassificationRawDataLoader
+from ....data.typing import Sample
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -46,7 +46,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
load_rc().get(config_variable, os.path.realpath(os.curdir)),
)
- def sample(self, sample: tuple[str, int]) -> Sample:
+ def sample(self, sample: tuple[str, int, typing.Any | None]) -> Sample:
"""Load a single image sample from the disk.
Parameters
@@ -74,12 +74,12 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
return tensor, dict(target=sample[1], name=sample[0]) # type: ignore[arg-type]
- def target(self, sample: tuple[str, int]) -> int:
+ def target(self, k: typing.Any) -> int | list[int]:
"""Load a single image sample target from the disk.
Parameters
----------
- sample
+ k
A tuple containing the path suffix, within the dataset root folder,
where to find the image to be loaded, and an integer, representing
the sample target.
@@ -90,7 +90,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
The integer target associated with the sample.
"""
- return sample[1]
+ return k[1]
class DataModule(CachingDataModule):
@@ -140,4 +140,5 @@ class DataModule(CachingDataModule):
raw_data_loader=ClassificationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/montgomery/default.json b/src/mednet/classify/config/data/montgomery/default.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/default.json
rename to src/mednet/classify/config/data/montgomery/default.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/default.py b/src/mednet/classify/config/data/montgomery/default.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/montgomery/default.py
rename to src/mednet/classify/config/data/montgomery/default.py
index 81bbe384..15b24126 100644
--- a/src/mednet/libs/classification/config/data/montgomery/default.py
+++ b/src/mednet/classify/config/data/montgomery/default.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.montgomery.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold-0.json b/src/mednet/classify/config/data/montgomery/fold-0.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/fold-0.json
rename to src/mednet/classify/config/data/montgomery/fold-0.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold-1.json b/src/mednet/classify/config/data/montgomery/fold-1.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/fold-1.json
rename to src/mednet/classify/config/data/montgomery/fold-1.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold-2.json b/src/mednet/classify/config/data/montgomery/fold-2.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/fold-2.json
rename to src/mednet/classify/config/data/montgomery/fold-2.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold-3.json b/src/mednet/classify/config/data/montgomery/fold-3.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/fold-3.json
rename to src/mednet/classify/config/data/montgomery/fold-3.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold-4.json b/src/mednet/classify/config/data/montgomery/fold-4.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/fold-4.json
rename to src/mednet/classify/config/data/montgomery/fold-4.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold-5.json b/src/mednet/classify/config/data/montgomery/fold-5.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/fold-5.json
rename to src/mednet/classify/config/data/montgomery/fold-5.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold-6.json b/src/mednet/classify/config/data/montgomery/fold-6.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/fold-6.json
rename to src/mednet/classify/config/data/montgomery/fold-6.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold-7.json b/src/mednet/classify/config/data/montgomery/fold-7.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/fold-7.json
rename to src/mednet/classify/config/data/montgomery/fold-7.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold-8.json b/src/mednet/classify/config/data/montgomery/fold-8.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/fold-8.json
rename to src/mednet/classify/config/data/montgomery/fold-8.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold-9.json b/src/mednet/classify/config/data/montgomery/fold-9.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery/fold-9.json
rename to src/mednet/classify/config/data/montgomery/fold-9.json
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold_0.py b/src/mednet/classify/config/data/montgomery/fold_0.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery/fold_0.py
rename to src/mednet/classify/config/data/montgomery/fold_0.py
index 97f677e6..d7eb6b8c 100644
--- a/src/mednet/libs/classification/config/data/montgomery/fold_0.py
+++ b/src/mednet/classify/config/data/montgomery/fold_0.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
-technical details.
+See :py:class:`mednet.classify.config.data.montgomery.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("fold-0.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold_1.py b/src/mednet/classify/config/data/montgomery/fold_1.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery/fold_1.py
rename to src/mednet/classify/config/data/montgomery/fold_1.py
index 383d0cde..029dfee6 100644
--- a/src/mednet/libs/classification/config/data/montgomery/fold_1.py
+++ b/src/mednet/classify/config/data/montgomery/fold_1.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
-technical details.
+See :py:class:`mednet.classify.config.data.montgomery.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("fold-1.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold_2.py b/src/mednet/classify/config/data/montgomery/fold_2.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery/fold_2.py
rename to src/mednet/classify/config/data/montgomery/fold_2.py
index 5ee16a95..c02a07ee 100644
--- a/src/mednet/libs/classification/config/data/montgomery/fold_2.py
+++ b/src/mednet/classify/config/data/montgomery/fold_2.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
-technical details.
+See :py:class:`mednet.classify.config.data.montgomery.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("fold-2.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold_3.py b/src/mednet/classify/config/data/montgomery/fold_3.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery/fold_3.py
rename to src/mednet/classify/config/data/montgomery/fold_3.py
index 9fb4a68e..9deeec34 100644
--- a/src/mednet/libs/classification/config/data/montgomery/fold_3.py
+++ b/src/mednet/classify/config/data/montgomery/fold_3.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
-technical details.
+See :py:class:`mednet.classify.config.data.montgomery.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("fold-3.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold_4.py b/src/mednet/classify/config/data/montgomery/fold_4.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery/fold_4.py
rename to src/mednet/classify/config/data/montgomery/fold_4.py
index 050b2986..4f501fbb 100644
--- a/src/mednet/libs/classification/config/data/montgomery/fold_4.py
+++ b/src/mednet/classify/config/data/montgomery/fold_4.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
-technical details.
+See :py:class:`mednet.classify.config.data.montgomery.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("fold-4.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold_5.py b/src/mednet/classify/config/data/montgomery/fold_5.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery/fold_5.py
rename to src/mednet/classify/config/data/montgomery/fold_5.py
index fddac647..144771ee 100644
--- a/src/mednet/libs/classification/config/data/montgomery/fold_5.py
+++ b/src/mednet/classify/config/data/montgomery/fold_5.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
-technical details.
+See :py:class:`mednet.classify.config.data.montgomery.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("fold-5.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold_6.py b/src/mednet/classify/config/data/montgomery/fold_6.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery/fold_6.py
rename to src/mednet/classify/config/data/montgomery/fold_6.py
index 5c8a72a4..305aaa46 100644
--- a/src/mednet/libs/classification/config/data/montgomery/fold_6.py
+++ b/src/mednet/classify/config/data/montgomery/fold_6.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
-technical details.
+See :py:class:`mednet.classify.config.data.montgomery.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("fold-6.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold_7.py b/src/mednet/classify/config/data/montgomery/fold_7.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery/fold_7.py
rename to src/mednet/classify/config/data/montgomery/fold_7.py
index 123b1afa..08490dcb 100644
--- a/src/mednet/libs/classification/config/data/montgomery/fold_7.py
+++ b/src/mednet/classify/config/data/montgomery/fold_7.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
-technical details.
+See :py:class:`mednet.classify.config.data.montgomery.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("fold-7.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold_8.py b/src/mednet/classify/config/data/montgomery/fold_8.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery/fold_8.py
rename to src/mednet/classify/config/data/montgomery/fold_8.py
index 53b9999e..ce4b4521 100644
--- a/src/mednet/libs/classification/config/data/montgomery/fold_8.py
+++ b/src/mednet/classify/config/data/montgomery/fold_8.py
@@ -5,12 +5,11 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
-technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("fold-8.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery/fold_9.py b/src/mednet/classify/config/data/montgomery/fold_9.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery/fold_9.py
rename to src/mednet/classify/config/data/montgomery/fold_9.py
index b09a83ed..7e8fca38 100644
--- a/src/mednet/libs/classification/config/data/montgomery/fold_9.py
+++ b/src/mednet/classify/config/data/montgomery/fold_9.py
@@ -5,12 +5,11 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.montgomery.datamodule.DataModule` for
-technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("fold-9.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/__init__.py b/src/mednet/classify/config/data/montgomery_shenzhen/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/__init__.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/__init__.py
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/datamodule.py b/src/mednet/classify/config/data/montgomery_shenzhen/datamodule.py
similarity index 89%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/datamodule.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/datamodule.py
index cce90f7a..9ce86de8 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/datamodule.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/datamodule.py
@@ -5,12 +5,9 @@
import pathlib
-from mednet.libs.common.data.datamodule import ConcatDataModule
-from mednet.libs.common.data.split import make_split
-
-from ..montgomery.datamodule import (
- ClassificationRawDataLoader as MontgomeryLoader,
-)
+from .....data.datamodule import ConcatDataModule
+from .....data.split import make_split
+from ..montgomery.datamodule import ClassificationRawDataLoader as MontgomeryLoader
from ..shenzhen.datamodule import ClassificationRawDataLoader as ShenzhenLoader
@@ -49,4 +46,5 @@ class DataModule(ConcatDataModule):
},
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/default.py b/src/mednet/classify/config/data/montgomery_shenzhen/default.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/default.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/default.py
index bfa3b4fa..b000fa45 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/default.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/default.py
@@ -4,10 +4,12 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (default
split).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_0.py b/src/mednet/classify/config/data/montgomery_shenzhen/fold_0.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_0.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/fold_0.py
index 645d2c57..2ea47510 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_0.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/fold_0.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (cross
validation fold 0).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import DataModule
datamodule = DataModule("fold-0.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_1.py b/src/mednet/classify/config/data/montgomery_shenzhen/fold_1.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_1.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/fold_1.py
index 9f05c713..586a816e 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_1.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/fold_1.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (cross
validation fold 1).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import DataModule
datamodule = DataModule("fold-1.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_2.py b/src/mednet/classify/config/data/montgomery_shenzhen/fold_2.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_2.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/fold_2.py
index 16e3ef9f..8e465b90 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_2.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/fold_2.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (cross
validation fold 2).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import DataModule
datamodule = DataModule("fold-2.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_3.py b/src/mednet/classify/config/data/montgomery_shenzhen/fold_3.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_3.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/fold_3.py
index 2d1404fb..81e71d11 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_3.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/fold_3.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (cross
validation fold 3).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import DataModule
datamodule = DataModule("fold-3.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_4.py b/src/mednet/classify/config/data/montgomery_shenzhen/fold_4.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_4.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/fold_4.py
index 25e9a4e9..2494ad07 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_4.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/fold_4.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (cross
validation fold 4).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import DataModule
datamodule = DataModule("fold-4.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_5.py b/src/mednet/classify/config/data/montgomery_shenzhen/fold_5.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_5.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/fold_5.py
index c5533299..dec5701d 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_5.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/fold_5.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (cross
validation fold 5).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import DataModule
datamodule = DataModule("fold-5.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_6.py b/src/mednet/classify/config/data/montgomery_shenzhen/fold_6.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_6.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/fold_6.py
index 42300375..e2feb847 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_6.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/fold_6.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (cross
validation fold 6).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import DataModule
datamodule = DataModule("fold-6.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_7.py b/src/mednet/classify/config/data/montgomery_shenzhen/fold_7.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_7.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/fold_7.py
index 296f3e57..c78b4b24 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_7.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/fold_7.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (cross
validation fold 7).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import DataModule
datamodule = DataModule("fold-7.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_8.py b/src/mednet/classify/config/data/montgomery_shenzhen/fold_8.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_8.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/fold_8.py
index 3428c0fb..0e1e1e65 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_8.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/fold_8.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (cross
validation fold 8).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import DataModule
datamodule = DataModule("fold-8.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_9.py b/src/mednet/classify/config/data/montgomery_shenzhen/fold_9.py
similarity index 59%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_9.py
rename to src/mednet/classify/config/data/montgomery_shenzhen/fold_9.py
index 219ee6f3..6386a0e2 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen/fold_9.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen/fold_9.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery and Shenzhen datasets (cross
validation fold 9).
-See :py:class:`.montgomery_shenzhen.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen.datamodule import DataModule
datamodule = DataModule("fold-9.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_padchest/__init__.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_padchest/__init__.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/__init__.py
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/datamodule.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/datamodule.py
similarity index 91%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/datamodule.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/datamodule.py
index 2f6caeac..39943fce 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/datamodule.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/datamodule.py
@@ -7,15 +7,12 @@ databases.
import pathlib
-from mednet.libs.common.data.datamodule import ConcatDataModule
-from mednet.libs.common.data.split import make_split
-
+from .....data.datamodule import ConcatDataModule
+from .....data.split import make_split
from ..indian.datamodule import CONFIGURATION_KEY_DATADIR as INDIAN_KEY_DATADIR
from ..indian.datamodule import ClassificationRawDataLoader as IndianLoader
from ..indian.datamodule import DataModule as IndianDataModule
-from ..montgomery.datamodule import (
- ClassificationRawDataLoader as MontgomeryLoader,
-)
+from ..montgomery.datamodule import ClassificationRawDataLoader as MontgomeryLoader
from ..shenzhen.datamodule import ClassificationRawDataLoader as ShenzhenLoader
@@ -61,4 +58,5 @@ class DataModule(ConcatDataModule):
},
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/default.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/default.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/default.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/default.py
index eff34ad7..c40448d9 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/default.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/default.py
@@ -3,11 +3,12 @@
# SPDX-License-Identifier: GPL-3.0-or-later
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets.
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical
-details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_0.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_0.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_0.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_0.py
index 6698f909..7f992977 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_0.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_0.py
@@ -4,12 +4,11 @@
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets
(cross validation fold 0).
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical
-details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import DataModule
datamodule = DataModule("fold-0.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_1.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_1.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_1.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_1.py
index 508b6e0a..0dafee66 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_1.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_1.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets
(cross validation fold 1).
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import DataModule
datamodule = DataModule("fold-1.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_2.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_2.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_2.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_2.py
index b9961c68..b4de05fe 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_2.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_2.py
@@ -4,12 +4,11 @@
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets
(cross validation fold 2).
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical
-details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import DataModule
datamodule = DataModule("fold-2.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_3.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_3.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_3.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_3.py
index 3b842210..e3199882 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_3.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_3.py
@@ -4,12 +4,11 @@
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets
(cross validation fold 3).
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical
-details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import DataModule
datamodule = DataModule("fold-3.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_4.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_4.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_4.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_4.py
index 8c8b1011..71942d55 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_4.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_4.py
@@ -4,12 +4,11 @@
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets
(cross validation fold 4).
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical
-details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import DataModule
datamodule = DataModule("fold-4.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_5.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_5.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_5.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_5.py
index ff53aa9b..14556919 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_5.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_5.py
@@ -4,12 +4,11 @@
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets
(cross validation fold 5).
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical
-details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import DataModule
datamodule = DataModule("fold-5.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_6.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_6.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_6.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_6.py
index 4e0ba18d..d6c0cc23 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_6.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_6.py
@@ -4,12 +4,11 @@
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets
(cross validation fold 6).
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical
-details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import DataModule
datamodule = DataModule("fold-6.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_7.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_7.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_7.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_7.py
index 1251045f..f16c32f6 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_7.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_7.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets
(cross validation fold 7).
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import DataModule
datamodule = DataModule("fold-7.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_8.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_8.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_8.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_8.py
index 3f87a0cd..0b8f10c7 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_8.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_8.py
@@ -4,12 +4,11 @@
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets
(cross validation fold 8).
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical
-details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import DataModule
datamodule = DataModule("fold-8.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_9.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_9.py
similarity index 58%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_9.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_9.py
index 425c1ca4..a1386f85 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian/fold_9.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian/fold_9.py
@@ -4,11 +4,11 @@
"""Aggregated DataModule composed of Montgomery, Shenzhen and Indian datasets
(cross validation fold 9).
-See :py:class:`.montgomery_shenzhen_indian.datamodule.DataModule` for technical details.
+See
+:py:class:`mednet.classify.config.data.montgomery_shenzhen_indian.datamodule.DataModule`
+for technical details.
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.montgomery_shenzhen_indian.datamodule import DataModule
datamodule = DataModule("fold-9.json")
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/__init__.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_padchest/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/__init__.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_padchest/__init__.py
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_padchest/datamodule.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_padchest/datamodule.py
similarity index 93%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_padchest/datamodule.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_padchest/datamodule.py
index 5daef812..1486e7b4 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_padchest/datamodule.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_padchest/datamodule.py
@@ -7,15 +7,12 @@ datasets.
import pathlib
-from mednet.libs.common.data.datamodule import ConcatDataModule
-from mednet.libs.common.data.split import make_split
-
+from .....data.datamodule import ConcatDataModule
+from .....data.split import make_split
from ..indian.datamodule import CONFIGURATION_KEY_DATADIR as INDIAN_KEY_DATADIR
from ..indian.datamodule import ClassificationRawDataLoader as IndianLoader
from ..indian.datamodule import DataModule as IndianDataModule
-from ..montgomery.datamodule import (
- ClassificationRawDataLoader as MontgomeryLoader,
-)
+from ..montgomery.datamodule import ClassificationRawDataLoader as MontgomeryLoader
from ..padchest.datamodule import ClassificationRawDataLoader as PadchestLoader
from ..shenzhen.datamodule import ClassificationRawDataLoader as ShenzhenLoader
@@ -75,4 +72,5 @@ class DataModule(ConcatDataModule):
+ "+"
+ pathlib.Path(padchest_split_filename).stem
),
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_padchest/default.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_padchest/default.py
similarity index 73%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_padchest/default.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_padchest/default.py
index 04b74eca..b3ed33c8 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_padchest/default.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_padchest/default.py
@@ -3,7 +3,7 @@
# SPDX-License-Identifier: GPL-3.0-or-later
"""Aggregated dataset composed of Montgomery, Shenzhen, Indian and Padchest datasets."""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_padchest.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_padchest.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/nih_cxr14/__init__.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/nih_cxr14/__init__.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/__init__.py
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/datamodule.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/datamodule.py
similarity index 93%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/datamodule.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/datamodule.py
index c83680ec..a8d1b216 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/datamodule.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/datamodule.py
@@ -7,15 +7,12 @@ datasets.
import pathlib
-from mednet.libs.common.data.datamodule import ConcatDataModule
-from mednet.libs.common.data.split import make_split
-
+from .....data.datamodule import ConcatDataModule
+from .....data.split import make_split
from ..indian.datamodule import CONFIGURATION_KEY_DATADIR as INDIAN_KEY_DATADIR
from ..indian.datamodule import ClassificationRawDataLoader as IndianLoader
from ..indian.datamodule import DataModule as IndianDataModule
-from ..montgomery.datamodule import (
- ClassificationRawDataLoader as MontgomeryLoader,
-)
+from ..montgomery.datamodule import ClassificationRawDataLoader as MontgomeryLoader
from ..shenzhen.datamodule import ClassificationRawDataLoader as ShenzhenLoader
from ..tbx11k.datamodule import ClassificationRawDataLoader as TBX11kLoader
@@ -74,4 +71,5 @@ class DataModule(ConcatDataModule):
+ "+"
+ pathlib.Path(tbx11k_split_filename).stem
),
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_0.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_0.py
similarity index 82%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_0.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_0.py
index 9e7a10ea..cf81872d 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_0.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_0.py
@@ -8,7 +8,7 @@ This remix dataset combines ``fold-0`` from Montgomery, Shenzhen, and Indian
datasets with ``v1-fold-0`` of TBX11k (healthy vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_1.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_1.py
similarity index 82%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_1.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_1.py
index 9ab338ce..8fb78d73 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_1.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_1.py
@@ -8,7 +8,7 @@ This remix dataset combines ``fold-1`` from Montgomery, Shenzhen, and Indian
datasets with ``v1-fold-1`` of TBX11k (healthy vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_2.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_2.py
similarity index 82%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_2.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_2.py
index 25c7367e..982fafbe 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_2.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_2.py
@@ -8,7 +8,7 @@ This remix dataset combines ``fold-2`` from Montgomery, Shenzhen, and Indian
datasets with ``v1-fold-2`` of TBX11k (healthy vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_3.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_3.py
similarity index 82%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_3.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_3.py
index e86ab293..b18001b7 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_3.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_3.py
@@ -8,7 +8,7 @@ This remix dataset combines ``fold-3`` from Montgomery, Shenzhen, and Indian
datasets with ``v1-fold-3`` of TBX11k (healthy vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_4.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_4.py
similarity index 82%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_4.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_4.py
index fe968cf8..c60c60b2 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_4.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_4.py
@@ -8,7 +8,7 @@ This remix dataset combines ``fold-4`` from Montgomery, Shenzhen, and Indian
datasets with ``v1-fold-4`` of TBX11k (healthy vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_5.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_5.py
similarity index 82%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_5.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_5.py
index 28b0b822..f62db63a 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_5.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_5.py
@@ -8,7 +8,7 @@ This remix dataset combines ``fold-5`` from Montgomery, Shenzhen, and Indian
datasets with ``v1-fold-5`` of TBX11k (healthy vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_6.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_6.py
similarity index 82%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_6.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_6.py
index 0986a1c5..fde8d157 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_6.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_6.py
@@ -8,7 +8,7 @@ This remix dataset combines ``fold-6`` from Montgomery, Shenzhen, and Indian
datasets with ``v1-fold-6`` of TBX11k (healthy vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_7.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_7.py
similarity index 82%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_7.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_7.py
index 051841a5..8e398c7f 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_7.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_7.py
@@ -8,7 +8,7 @@ This remix dataset combines ``fold-7`` from Montgomery, Shenzhen, and Indian
datasets with ``v1-fold-7`` of TBX11k (healthy vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_8.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_8.py
similarity index 82%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_8.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_8.py
index 9c9e7be4..887d47b4 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_8.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_8.py
@@ -8,7 +8,7 @@ This remix dataset combines ``fold-8`` from Montgomery, Shenzhen, and Indian
datasets with ``v1-fold-8`` of TBX11k (healthy vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_9.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_9.py
similarity index 82%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_9.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_9.py
index 3ccf2910..8e54fc38 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_9.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_fold_9.py
@@ -8,7 +8,7 @@ This remix dataset combines ``fold-9`` from Montgomery, Shenzhen, and Indian
datasets with ``v1-fold-9`` of TBX11k (healthy vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_healthy_vs_atb.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_healthy_vs_atb.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_healthy_vs_atb.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_healthy_vs_atb.py
index c30b2bbb..21f266b6 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v1_healthy_vs_atb.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v1_healthy_vs_atb.py
@@ -9,7 +9,7 @@ and Indian datasets with ``v1-healthy-vs-atb`` split of TBX11k (healthy vs.
active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_0.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_0.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_0.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_0.py
index a959fa5c..f2e13a6a 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_0.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_0.py
@@ -9,7 +9,7 @@ datasets with ``v2-fold-0`` of TBX11k (healthy, sick and latent TB vs. active
TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_1.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_1.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_1.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_1.py
index fed9f395..fc6760f8 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_1.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_1.py
@@ -9,7 +9,7 @@ datasets with ``v2-fold-1`` of TBX11k (healthy, sick and latent TB vs. active
TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_2.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_2.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_2.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_2.py
index be946b8d..63ff17f4 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_2.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_2.py
@@ -9,7 +9,7 @@ datasets with ``v2-fold-2`` of TBX11k (healthy, sick and latent TB vs. active
TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_3.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_3.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_3.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_3.py
index 3c8a8bed..fab9be82 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_3.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_3.py
@@ -9,7 +9,7 @@ datasets with ``v2-fold-3`` of TBX11k (healthy, sick and latent TB vs. active
TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_4.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_4.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_4.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_4.py
index 5cfc0dac..0c740d2c 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_4.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_4.py
@@ -9,7 +9,7 @@ datasets with ``v2-fold-4`` of TBX11k (healthy, sick and latent TB vs. active
TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_5.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_5.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_5.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_5.py
index 02a01229..5e7a394f 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_5.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_5.py
@@ -9,7 +9,7 @@ datasets with ``v2-fold-5`` of TBX11k (healthy, sick and latent TB vs. active
TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_6.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_6.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_6.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_6.py
index 2dff3c16..0326de12 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_6.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_6.py
@@ -9,7 +9,7 @@ datasets with ``v2-fold-6`` of TBX11k (healthy, sick and latent TB vs. active
TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_7.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_7.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_7.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_7.py
index 17f05110..ada0b286 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_7.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_7.py
@@ -9,7 +9,7 @@ datasets with ``v2-fold-7`` of TBX11k (healthy, sick and latent TB vs. active
TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_8.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_8.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_8.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_8.py
index aaf80c97..52362f97 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_8.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_8.py
@@ -9,7 +9,7 @@ datasets with ``v2-fold-8`` of TBX11k (healthy, sick and latent TB vs. active
TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_9.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_9.py
similarity index 83%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_9.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_9.py
index 8b17d320..bb364898 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_9.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_fold_9.py
@@ -9,7 +9,7 @@ datasets with ``v2-fold-9`` of TBX11k (healthy, sick and latent TB vs. active
TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_others_vs_atb.py b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_others_vs_atb.py
similarity index 84%
rename from src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_others_vs_atb.py
rename to src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_others_vs_atb.py
index 6c0ab4e7..36d088de 100644
--- a/src/mednet/libs/classification/config/data/montgomery_shenzhen_indian_tbx11k/v2_others_vs_atb.py
+++ b/src/mednet/classify/config/data/montgomery_shenzhen_indian_tbx11k/v2_others_vs_atb.py
@@ -9,7 +9,7 @@ and Indian datasets with ``v2-others-vs-atb`` of TBX11k (healthy, sick and
latent TB vs. active TB samples).
"""
-from mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
+from mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/nih_cxr14_padchest/__init__.py b/src/mednet/classify/config/data/nih_cxr14/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/nih_cxr14_padchest/__init__.py
rename to src/mednet/classify/config/data/nih_cxr14/__init__.py
diff --git a/src/mednet/libs/classification/config/data/nih_cxr14/cardiomegaly.json b/src/mednet/classify/config/data/nih_cxr14/cardiomegaly.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/nih_cxr14/cardiomegaly.json
rename to src/mednet/classify/config/data/nih_cxr14/cardiomegaly.json
diff --git a/src/mednet/libs/classification/config/data/nih_cxr14/cardiomegaly.py b/src/mednet/classify/config/data/nih_cxr14/cardiomegaly.py
similarity index 68%
rename from src/mednet/libs/classification/config/data/nih_cxr14/cardiomegaly.py
rename to src/mednet/classify/config/data/nih_cxr14/cardiomegaly.py
index 30c23c2a..205c3f18 100644
--- a/src/mednet/libs/classification/config/data/nih_cxr14/cardiomegaly.py
+++ b/src/mednet/classify/config/data/nih_cxr14/cardiomegaly.py
@@ -8,12 +8,10 @@ Database reference: [NIH-CXR14-2017]_
This split contains cardiomegaly cases from the NIH CXR14 database.
-See :py:class:`mednet.libs.classification.config.data.nih_cxr14.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.nih_cxr14.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.nih_cxr14.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.nih_cxr14.datamodule import DataModule
datamodule = DataModule("cardiomegaly.json")
diff --git a/src/mednet/libs/classification/config/data/nih_cxr14/datamodule.py b/src/mednet/classify/config/data/nih_cxr14/datamodule.py
similarity index 91%
rename from src/mednet/libs/classification/config/data/nih_cxr14/datamodule.py
rename to src/mednet/classify/config/data/nih_cxr14/datamodule.py
index 719a78ad..b2585006 100644
--- a/src/mednet/libs/classification/config/data/nih_cxr14/datamodule.py
+++ b/src/mednet/classify/config/data/nih_cxr14/datamodule.py
@@ -8,17 +8,17 @@ Database reference: [NIH-CXR14-2017]_
import os
import pathlib
+import typing
import PIL.Image
-from mednet.libs.classification.data.typing import (
- ClassificationRawDataLoader as _ClassificationRawDataLoader,
-)
-from mednet.libs.classification.data.typing import Sample
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import ClassificationRawDataLoader as _ClassificationRawDataLoader
+from ....data.typing import Sample
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database.
@@ -63,7 +63,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
False,
)
- def sample(self, sample: tuple[str, list[int]]) -> Sample:
+ def sample(self, sample: tuple[str, int, typing.Any | None]) -> Sample:
"""Load a single image sample from the disk.
Parameters
@@ -100,12 +100,12 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
return tensor, dict(target=sample[1], name=sample[0]) # type: ignore[arg-type]
- def target(self, sample: tuple[str, list[int]]) -> list[int]:
+ def target(self, k: typing.Any) -> int | list[int]:
"""Load a single image sample target from the disk.
Parameters
----------
- sample
+ k
A tuple containing the path suffix, within the dataset root folder,
where to find the image to be loaded, and an integer, representing the
sample target.
@@ -116,7 +116,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
The integer targets associated with the sample.
"""
- return sample[1]
+ return k[1]
class DataModule(CachingDataModule):
@@ -178,4 +178,5 @@ class DataModule(CachingDataModule):
raw_data_loader=ClassificationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/nih_cxr14/default.json.bz2 b/src/mednet/classify/config/data/nih_cxr14/default.json.bz2
similarity index 100%
rename from src/mednet/libs/classification/config/data/nih_cxr14/default.json.bz2
rename to src/mednet/classify/config/data/nih_cxr14/default.json.bz2
diff --git a/src/mednet/libs/classification/config/data/nih_cxr14/default.py b/src/mednet/classify/config/data/nih_cxr14/default.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/nih_cxr14/default.py
rename to src/mednet/classify/config/data/nih_cxr14/default.py
index 80b8df23..3adaa3cc 100644
--- a/src/mednet/libs/classification/config/data/nih_cxr14/default.py
+++ b/src/mednet/classify/config/data/nih_cxr14/default.py
@@ -7,12 +7,10 @@
* Validation samples: 6350
* Test samples: 4054
-See :py:class:`mednet.libs.classification.config.data.nih_cxr14.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.nih_cxr14.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.nih_cxr14.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.nih_cxr14.datamodule import DataModule
datamodule = DataModule("default.json.bz2")
diff --git a/src/mednet/libs/classification/config/data/padchest/__init__.py b/src/mednet/classify/config/data/nih_cxr14_padchest/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/padchest/__init__.py
rename to src/mednet/classify/config/data/nih_cxr14_padchest/__init__.py
diff --git a/src/mednet/libs/classification/config/data/nih_cxr14_padchest/datamodule.py b/src/mednet/classify/config/data/nih_cxr14_padchest/datamodule.py
similarity index 94%
rename from src/mednet/libs/classification/config/data/nih_cxr14_padchest/datamodule.py
rename to src/mednet/classify/config/data/nih_cxr14_padchest/datamodule.py
index e1907a35..1ad11a53 100644
--- a/src/mednet/libs/classification/config/data/nih_cxr14_padchest/datamodule.py
+++ b/src/mednet/classify/config/data/nih_cxr14_padchest/datamodule.py
@@ -5,9 +5,8 @@
import pathlib
-from mednet.libs.common.data.datamodule import ConcatDataModule
-from mednet.libs.common.data.split import make_split
-
+from .....data.datamodule import ConcatDataModule
+from .....data.split import make_split
from ..nih_cxr14.datamodule import ClassificationRawDataLoader as CXR14Loader
from ..padchest.datamodule import ClassificationRawDataLoader as PadchestLoader
@@ -55,4 +54,5 @@ class DataModule(ConcatDataModule):
+ "+"
+ pathlib.Path(padchest_split_filename).stem
),
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/nih_cxr14_padchest/idiap.py b/src/mednet/classify/config/data/nih_cxr14_padchest/idiap.py
similarity index 80%
rename from src/mednet/libs/classification/config/data/nih_cxr14_padchest/idiap.py
rename to src/mednet/classify/config/data/nih_cxr14_padchest/idiap.py
index 86e44dca..db926c53 100644
--- a/src/mednet/libs/classification/config/data/nih_cxr14_padchest/idiap.py
+++ b/src/mednet/classify/config/data/nih_cxr14_padchest/idiap.py
@@ -5,7 +5,7 @@
(no-tb-idiap split).
"""
-from mednet.libs.classification.config.data.nih_cxr14_padchest.datamodule import (
+from mednet.classify.config.data.nih_cxr14_padchest.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/shenzhen/__init__.py b/src/mednet/classify/config/data/padchest/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/__init__.py
rename to src/mednet/classify/config/data/padchest/__init__.py
diff --git a/src/mednet/libs/classification/config/data/padchest/cardiomegaly-idiap.json b/src/mednet/classify/config/data/padchest/cardiomegaly-idiap.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/padchest/cardiomegaly-idiap.json
rename to src/mednet/classify/config/data/padchest/cardiomegaly-idiap.json
diff --git a/src/mednet/libs/classification/config/data/padchest/cardiomegaly_idiap.py b/src/mednet/classify/config/data/padchest/cardiomegaly_idiap.py
similarity index 72%
rename from src/mednet/libs/classification/config/data/padchest/cardiomegaly_idiap.py
rename to src/mednet/classify/config/data/padchest/cardiomegaly_idiap.py
index 9b4dd7e6..af0923bc 100644
--- a/src/mednet/libs/classification/config/data/padchest/cardiomegaly_idiap.py
+++ b/src/mednet/classify/config/data/padchest/cardiomegaly_idiap.py
@@ -9,12 +9,10 @@ This split contains the first 40 images with cardiomegaly, with parameters:
Label = "Normal", MethodLabel = "Physician", Projection = "PA"
Read documentation of
-:py:class:`mednet.libs.classification.config.data.padchest.datamodule.DataModule` for technical
+:py:class:`mednet.classify.config.data.padchest.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.padchest.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.padchest.datamodule import DataModule
datamodule = DataModule("cardiomegaly-idiap.json")
diff --git a/src/mednet/libs/classification/config/data/padchest/datamodule.py b/src/mednet/classify/config/data/padchest/datamodule.py
similarity index 94%
rename from src/mednet/libs/classification/config/data/padchest/datamodule.py
rename to src/mednet/classify/config/data/padchest/datamodule.py
index 20f6e221..669ac2c4 100644
--- a/src/mednet/libs/classification/config/data/padchest/datamodule.py
+++ b/src/mednet/classify/config/data/padchest/datamodule.py
@@ -8,19 +8,19 @@ Database reference: [PADCHEST-2019]_
import os
import pathlib
+import typing
import numpy
import PIL.Image
-from mednet.libs.classification.data.typing import (
- ClassificationRawDataLoader as _ClassificationRawDataLoader,
-)
-from mednet.libs.classification.data.typing import Sample
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.image_utils import remove_black_borders
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.image_utils import remove_black_borders
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import ClassificationRawDataLoader as _ClassificationRawDataLoader
+from ....data.typing import Sample
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -41,7 +41,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
),
)
- def sample(self, sample: tuple[str, int | list[int]]) -> Sample:
+ def sample(self, sample: tuple[str, int, typing.Any | None]) -> Sample:
"""Load a single image sample from the disk.
Parameters
@@ -69,12 +69,12 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
return tensor, dict(target=sample[1], name=sample[0]) # type: ignore[arg-type]
- def target(self, sample: tuple[str, int | list[int]]) -> int | list[int]:
+ def target(self, k: typing.Any) -> int | list[int]:
"""Load a single image sample target from the disk.
Parameters
----------
- sample
+ k
A tuple containing the path suffix, within the dataset root folder,
where to find the image to be loaded, and an integer, representing
the sample target.
@@ -85,7 +85,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
The integer targets associated with the sample.
"""
- return sample[1]
+ return k[1]
class DataModule(CachingDataModule):
@@ -329,4 +329,5 @@ class DataModule(CachingDataModule):
raw_data_loader=ClassificationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/padchest/idiap.json.bz2 b/src/mednet/classify/config/data/padchest/idiap.json.bz2
similarity index 100%
rename from src/mednet/libs/classification/config/data/padchest/idiap.json.bz2
rename to src/mednet/classify/config/data/padchest/idiap.json.bz2
diff --git a/src/mednet/libs/classification/config/data/padchest/idiap.py b/src/mednet/classify/config/data/padchest/idiap.py
similarity index 71%
rename from src/mednet/libs/classification/config/data/padchest/idiap.py
rename to src/mednet/classify/config/data/padchest/idiap.py
index e1dd56c5..031c78c8 100644
--- a/src/mednet/libs/classification/config/data/padchest/idiap.py
+++ b/src/mednet/classify/config/data/padchest/idiap.py
@@ -6,7 +6,7 @@
Database reference: [PADCHEST-2019]_
This split contains all images in the database. Read documentation of
-:py:class:`mednet.libs.classification.config.data.padchest.datamodule.DataModule` for technical
+:py:class:`mednet.classify.config.data.padchest.datamodule.DataModule` for technical
details.
* Split reference: ours
@@ -15,8 +15,6 @@ details.
* Test samples: 0
"""
-from mednet.libs.classification.config.data.padchest.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.padchest.datamodule import DataModule
datamodule = DataModule("idiap.json.bz2")
diff --git a/src/mednet/libs/classification/config/data/padchest/no-tb-idiap.json.bz2 b/src/mednet/classify/config/data/padchest/no-tb-idiap.json.bz2
similarity index 100%
rename from src/mednet/libs/classification/config/data/padchest/no-tb-idiap.json.bz2
rename to src/mednet/classify/config/data/padchest/no-tb-idiap.json.bz2
diff --git a/src/mednet/libs/classification/config/data/padchest/no_tb_idiap.py b/src/mednet/classify/config/data/padchest/no_tb_idiap.py
similarity index 81%
rename from src/mednet/libs/classification/config/data/padchest/no_tb_idiap.py
rename to src/mednet/classify/config/data/padchest/no_tb_idiap.py
index 06159406..dc9c4df2 100644
--- a/src/mednet/libs/classification/config/data/padchest/no_tb_idiap.py
+++ b/src/mednet/classify/config/data/padchest/no_tb_idiap.py
@@ -29,11 +29,11 @@ Database reference: [PADCHEST-2019]_
* edema and consolidation
Read documentation of
-:py:class:`mednet.libs.classification.config.data.padchest.datamodule.DataModule` for technical
+:py:class:`mednet.classify.config.data.padchest.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.padchest.datamodule import (
+from mednet.classify.config.data.padchest.datamodule import (
DataModule,
)
diff --git a/src/mednet/libs/classification/config/data/padchest/tb-idiap.json b/src/mednet/classify/config/data/padchest/tb-idiap.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/padchest/tb-idiap.json
rename to src/mednet/classify/config/data/padchest/tb-idiap.json
diff --git a/src/mednet/libs/classification/config/data/padchest/tb_idiap.py b/src/mednet/classify/config/data/padchest/tb_idiap.py
similarity index 75%
rename from src/mednet/libs/classification/config/data/padchest/tb_idiap.py
rename to src/mednet/classify/config/data/padchest/tb_idiap.py
index c66decb6..6cfcb2dc 100644
--- a/src/mednet/libs/classification/config/data/padchest/tb_idiap.py
+++ b/src/mednet/classify/config/data/padchest/tb_idiap.py
@@ -11,12 +11,10 @@ Projection = "PA" and TB cases. Labelling matches those for active TB (binary)
classification datasets.
Read documentation of
-:py:class:`mednet.libs.classification.config.data.padchest.datamodule.DataModule` for technical
+:py:class:`mednet.classify.config.data.padchest.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.padchest.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.padchest.datamodule import DataModule
datamodule = DataModule("tb-idiap.json")
diff --git a/src/mednet/libs/classification/config/data/tbpoc/__init__.py b/src/mednet/classify/config/data/shenzhen/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/__init__.py
rename to src/mednet/classify/config/data/shenzhen/__init__.py
diff --git a/src/mednet/libs/classification/config/data/shenzhen/alltest.json b/src/mednet/classify/config/data/shenzhen/alltest.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/alltest.json
rename to src/mednet/classify/config/data/shenzhen/alltest.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/alltest.py b/src/mednet/classify/config/data/shenzhen/alltest.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/alltest.py
rename to src/mednet/classify/config/data/shenzhen/alltest.py
index 48b7d13a..c4d76e38 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/alltest.py
+++ b/src/mednet/classify/config/data/shenzhen/alltest.py
@@ -7,12 +7,10 @@ Database reference: [MONTGOMERY-SHENZHEN-2014]_
* Test samples: 100% of the database
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("alltest.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/datamodule.py b/src/mednet/classify/config/data/shenzhen/datamodule.py
similarity index 88%
rename from src/mednet/libs/classification/config/data/shenzhen/datamodule.py
rename to src/mednet/classify/config/data/shenzhen/datamodule.py
index 255d70b0..92f63575 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/datamodule.py
+++ b/src/mednet/classify/config/data/shenzhen/datamodule.py
@@ -8,18 +8,18 @@ Database reference: [MONTGOMERY-SHENZHEN-2014]_
import os
import pathlib
+import typing
import PIL.Image
-from mednet.libs.classification.data.typing import (
- ClassificationRawDataLoader as _ClassificationRawDataLoader,
-)
-from mednet.libs.classification.data.typing import Sample
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.image_utils import remove_black_borders
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.image_utils import remove_black_borders
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import ClassificationRawDataLoader as _ClassificationRawDataLoader
+from ....data.typing import Sample
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -46,7 +46,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
load_rc().get(config_variable, os.path.realpath(os.curdir)),
)
- def sample(self, sample: tuple[str, int]) -> Sample:
+ def sample(self, sample: tuple[str, int, typing.Any | None]) -> Sample:
"""Load a single image sample from the disk.
Parameters
@@ -74,12 +74,12 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
return tensor, dict(target=sample[1], name=sample[0]) # type: ignore[arg-type]
- def target(self, sample: tuple[str, int]) -> int:
+ def target(self, k: typing.Any) -> int | list[int]:
"""Load a single image sample target from the disk.
Parameters
----------
- sample
+ k
A tuple containing the path suffix, within the dataset root folder,
where to find the image to be loaded, and an integer, representing
the sample target.
@@ -90,7 +90,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
The integer target associated with the sample.
"""
- return sample[1]
+ return k[1]
class DataModule(CachingDataModule):
@@ -139,4 +139,5 @@ class DataModule(CachingDataModule):
raw_data_loader=ClassificationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/shenzhen/default.json b/src/mednet/classify/config/data/shenzhen/default.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/default.json
rename to src/mednet/classify/config/data/shenzhen/default.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/default.py b/src/mednet/classify/config/data/shenzhen/default.py
similarity index 72%
rename from src/mednet/libs/classification/config/data/shenzhen/default.py
rename to src/mednet/classify/config/data/shenzhen/default.py
index f3ee1926..20a877fb 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/default.py
+++ b/src/mednet/classify/config/data/shenzhen/default.py
@@ -9,12 +9,10 @@ Database reference: [MONTGOMERY-SHENZHEN-2014]_
* Validation samples: 16% of TB and healthy CXR (including labels)
* Test samples: 20% of TB and healthy CXR (including labels)
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold-0.json b/src/mednet/classify/config/data/shenzhen/fold-0.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/fold-0.json
rename to src/mednet/classify/config/data/shenzhen/fold-0.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold-1.json b/src/mednet/classify/config/data/shenzhen/fold-1.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/fold-1.json
rename to src/mednet/classify/config/data/shenzhen/fold-1.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold-2.json b/src/mednet/classify/config/data/shenzhen/fold-2.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/fold-2.json
rename to src/mednet/classify/config/data/shenzhen/fold-2.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold-3.json b/src/mednet/classify/config/data/shenzhen/fold-3.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/fold-3.json
rename to src/mednet/classify/config/data/shenzhen/fold-3.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold-4.json b/src/mednet/classify/config/data/shenzhen/fold-4.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/fold-4.json
rename to src/mednet/classify/config/data/shenzhen/fold-4.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold-5.json b/src/mednet/classify/config/data/shenzhen/fold-5.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/fold-5.json
rename to src/mednet/classify/config/data/shenzhen/fold-5.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold-6.json b/src/mednet/classify/config/data/shenzhen/fold-6.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/fold-6.json
rename to src/mednet/classify/config/data/shenzhen/fold-6.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold-7.json b/src/mednet/classify/config/data/shenzhen/fold-7.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/fold-7.json
rename to src/mednet/classify/config/data/shenzhen/fold-7.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold-8.json b/src/mednet/classify/config/data/shenzhen/fold-8.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/fold-8.json
rename to src/mednet/classify/config/data/shenzhen/fold-8.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold-9.json b/src/mednet/classify/config/data/shenzhen/fold-9.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/shenzhen/fold-9.json
rename to src/mednet/classify/config/data/shenzhen/fold-9.json
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold_0.py b/src/mednet/classify/config/data/shenzhen/fold_0.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/fold_0.py
rename to src/mednet/classify/config/data/shenzhen/fold_0.py
index 33ea121e..4401e33d 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/fold_0.py
+++ b/src/mednet/classify/config/data/shenzhen/fold_0.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("fold-0.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold_1.py b/src/mednet/classify/config/data/shenzhen/fold_1.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/fold_1.py
rename to src/mednet/classify/config/data/shenzhen/fold_1.py
index d34826c3..88c59af4 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/fold_1.py
+++ b/src/mednet/classify/config/data/shenzhen/fold_1.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("fold-1.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold_2.py b/src/mednet/classify/config/data/shenzhen/fold_2.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/fold_2.py
rename to src/mednet/classify/config/data/shenzhen/fold_2.py
index 67ad5d39..6863d702 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/fold_2.py
+++ b/src/mednet/classify/config/data/shenzhen/fold_2.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("fold-2.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold_3.py b/src/mednet/classify/config/data/shenzhen/fold_3.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/fold_3.py
rename to src/mednet/classify/config/data/shenzhen/fold_3.py
index 6534259a..bfe54b94 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/fold_3.py
+++ b/src/mednet/classify/config/data/shenzhen/fold_3.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("fold-3.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold_4.py b/src/mednet/classify/config/data/shenzhen/fold_4.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/fold_4.py
rename to src/mednet/classify/config/data/shenzhen/fold_4.py
index c4c02114..200a3aa4 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/fold_4.py
+++ b/src/mednet/classify/config/data/shenzhen/fold_4.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("fold-4.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold_5.py b/src/mednet/classify/config/data/shenzhen/fold_5.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/fold_5.py
rename to src/mednet/classify/config/data/shenzhen/fold_5.py
index a76c37c4..9c4eb7ef 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/fold_5.py
+++ b/src/mednet/classify/config/data/shenzhen/fold_5.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("fold-5.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold_6.py b/src/mednet/classify/config/data/shenzhen/fold_6.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/fold_6.py
rename to src/mednet/classify/config/data/shenzhen/fold_6.py
index eb464ebf..7eb18f4a 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/fold_6.py
+++ b/src/mednet/classify/config/data/shenzhen/fold_6.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("fold-6.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold_7.py b/src/mednet/classify/config/data/shenzhen/fold_7.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/fold_7.py
rename to src/mednet/classify/config/data/shenzhen/fold_7.py
index 43f35019..2d8a0f40 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/fold_7.py
+++ b/src/mednet/classify/config/data/shenzhen/fold_7.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("fold-7.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold_8.py b/src/mednet/classify/config/data/shenzhen/fold_8.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/fold_8.py
rename to src/mednet/classify/config/data/shenzhen/fold_8.py
index 776f7700..7b35e3d0 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/fold_8.py
+++ b/src/mednet/classify/config/data/shenzhen/fold_8.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("fold-8.json")
diff --git a/src/mednet/libs/classification/config/data/shenzhen/fold_9.py b/src/mednet/classify/config/data/shenzhen/fold_9.py
similarity index 64%
rename from src/mednet/libs/classification/config/data/shenzhen/fold_9.py
rename to src/mednet/classify/config/data/shenzhen/fold_9.py
index 351efa59..c079dea1 100644
--- a/src/mednet/libs/classification/config/data/shenzhen/fold_9.py
+++ b/src/mednet/classify/config/data/shenzhen/fold_9.py
@@ -5,12 +5,10 @@
Database reference: [MONTGOMERY-SHENZHEN-2014]_
-See :py:class:`mednet.libs.classification.config.data.shenzhen.datamodule.DataModule` for
+See :py:class:`mednet.classify.config.data.shenzhen.datamodule.DataModule` for
technical details.
"""
-from mednet.libs.classification.config.data.shenzhen.datamodule import (
- DataModule,
-)
+from mednet.classify.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("fold-9.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/__init__.py b/src/mednet/classify/config/data/tbpoc/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/__init__.py
rename to src/mednet/classify/config/data/tbpoc/__init__.py
diff --git a/src/mednet/libs/classification/config/data/tbpoc/datamodule.py b/src/mednet/classify/config/data/tbpoc/datamodule.py
similarity index 86%
rename from src/mednet/libs/classification/config/data/tbpoc/datamodule.py
rename to src/mednet/classify/config/data/tbpoc/datamodule.py
index 7d9c9bd8..ee95ebc5 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/datamodule.py
+++ b/src/mednet/classify/config/data/tbpoc/datamodule.py
@@ -4,18 +4,18 @@
import os
import pathlib
+import typing
import PIL.Image
-from mednet.libs.classification.data.typing import (
- ClassificationRawDataLoader as _ClassificationRawDataLoader,
-)
-from mednet.libs.classification.data.typing import Sample
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.image_utils import remove_black_borders
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.image_utils import remove_black_borders
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import ClassificationRawDataLoader as _ClassificationRawDataLoader
+from ....data.typing import Sample
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -36,7 +36,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
),
)
- def sample(self, sample: tuple[str, int]) -> Sample:
+ def sample(self, sample: tuple[str, int, typing.Any | None]) -> Sample:
"""Load a single image sample from the disk.
Parameters
@@ -62,7 +62,7 @@ class ClassificationRawDataLoader(_ClassificationRawDataLoader):
# to_pil_image(tensor).show()
# __import__("pdb").set_trace()
- return tensor, dict(target=sample[1], name=sample[0]) # type: ignore[arg-type]
+ return tensor, dict(target=sample[1], name=sample[0])
def target(self, sample: tuple[str, int]) -> int:
"""Load a single image sample target from the disk.
@@ -125,4 +125,5 @@ class DataModule(CachingDataModule):
raw_data_loader=ClassificationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold-0.json b/src/mednet/classify/config/data/tbpoc/fold-0.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/fold-0.json
rename to src/mednet/classify/config/data/tbpoc/fold-0.json
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold-1.json b/src/mednet/classify/config/data/tbpoc/fold-1.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/fold-1.json
rename to src/mednet/classify/config/data/tbpoc/fold-1.json
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold-2.json b/src/mednet/classify/config/data/tbpoc/fold-2.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/fold-2.json
rename to src/mednet/classify/config/data/tbpoc/fold-2.json
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold-3.json b/src/mednet/classify/config/data/tbpoc/fold-3.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/fold-3.json
rename to src/mednet/classify/config/data/tbpoc/fold-3.json
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold-4.json b/src/mednet/classify/config/data/tbpoc/fold-4.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/fold-4.json
rename to src/mednet/classify/config/data/tbpoc/fold-4.json
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold-5.json b/src/mednet/classify/config/data/tbpoc/fold-5.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/fold-5.json
rename to src/mednet/classify/config/data/tbpoc/fold-5.json
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold-6.json b/src/mednet/classify/config/data/tbpoc/fold-6.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/fold-6.json
rename to src/mednet/classify/config/data/tbpoc/fold-6.json
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold-7.json b/src/mednet/classify/config/data/tbpoc/fold-7.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/fold-7.json
rename to src/mednet/classify/config/data/tbpoc/fold-7.json
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold-8.json b/src/mednet/classify/config/data/tbpoc/fold-8.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/fold-8.json
rename to src/mednet/classify/config/data/tbpoc/fold-8.json
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold-9.json b/src/mednet/classify/config/data/tbpoc/fold-9.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbpoc/fold-9.json
rename to src/mednet/classify/config/data/tbpoc/fold-9.json
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold_0.py b/src/mednet/classify/config/data/tbpoc/fold_0.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/tbpoc/fold_0.py
rename to src/mednet/classify/config/data/tbpoc/fold_0.py
index 68c79c5c..82c0b134 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/fold_0.py
+++ b/src/mednet/classify/config/data/tbpoc/fold_0.py
@@ -5,10 +5,10 @@
Database reference: [TB-POC-2018]_
-See :py:class:`mednet.libs.classification.config.data.tbpoc.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbpoc.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbpoc.datamodule import DataModule
+from mednet.classify.config.data.tbpoc.datamodule import DataModule
datamodule = DataModule("fold-0.json")
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold_1.py b/src/mednet/classify/config/data/tbpoc/fold_1.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/tbpoc/fold_1.py
rename to src/mednet/classify/config/data/tbpoc/fold_1.py
index f33b24b7..910d030d 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/fold_1.py
+++ b/src/mednet/classify/config/data/tbpoc/fold_1.py
@@ -5,10 +5,10 @@
Database reference: [TB-POC-2018]_
-See :py:class:`mednet.libs.classification.config.data.tbpoc.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbpoc.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbpoc.datamodule import DataModule
+from mednet.classify.config.data.tbpoc.datamodule import DataModule
datamodule = DataModule("fold-1.json")
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold_2.py b/src/mednet/classify/config/data/tbpoc/fold_2.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/tbpoc/fold_2.py
rename to src/mednet/classify/config/data/tbpoc/fold_2.py
index 7ba9632d..f374f407 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/fold_2.py
+++ b/src/mednet/classify/config/data/tbpoc/fold_2.py
@@ -5,10 +5,10 @@
Database reference: [TB-POC-2018]_
-See :py:class:`mednet.libs.classification.config.data.tbpoc.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbpoc.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbpoc.datamodule import DataModule
+from mednet.classify.config.data.tbpoc.datamodule import DataModule
datamodule = DataModule("fold-2.json")
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold_3.py b/src/mednet/classify/config/data/tbpoc/fold_3.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/tbpoc/fold_3.py
rename to src/mednet/classify/config/data/tbpoc/fold_3.py
index 1c174c8a..b9c5ea7b 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/fold_3.py
+++ b/src/mednet/classify/config/data/tbpoc/fold_3.py
@@ -5,10 +5,10 @@
Database reference: [TB-POC-2018]_
-See :py:class:`mednet.libs.classification.config.data.tbpoc.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbpoc.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbpoc.datamodule import DataModule
+from mednet.classify.config.data.tbpoc.datamodule import DataModule
datamodule = DataModule("fold-3.json")
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold_4.py b/src/mednet/classify/config/data/tbpoc/fold_4.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/tbpoc/fold_4.py
rename to src/mednet/classify/config/data/tbpoc/fold_4.py
index e2f9ddd9..2c509831 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/fold_4.py
+++ b/src/mednet/classify/config/data/tbpoc/fold_4.py
@@ -5,10 +5,10 @@
Database reference: [TB-POC-2018]_
-See :py:class:`mednet.libs.classification.config.data.tbpoc.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbpoc.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbpoc.datamodule import DataModule
+from mednet.classify.config.data.tbpoc.datamodule import DataModule
datamodule = DataModule("fold-4.json")
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold_5.py b/src/mednet/classify/config/data/tbpoc/fold_5.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/tbpoc/fold_5.py
rename to src/mednet/classify/config/data/tbpoc/fold_5.py
index e8892641..b0414fe5 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/fold_5.py
+++ b/src/mednet/classify/config/data/tbpoc/fold_5.py
@@ -5,10 +5,10 @@
Database reference: [TB-POC-2018]_
-See :py:class:`mednet.libs.classification.config.data.tbpoc.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbpoc.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbpoc.datamodule import DataModule
+from mednet.classify.config.data.tbpoc.datamodule import DataModule
datamodule = DataModule("fold-5.json")
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold_6.py b/src/mednet/classify/config/data/tbpoc/fold_6.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/tbpoc/fold_6.py
rename to src/mednet/classify/config/data/tbpoc/fold_6.py
index 71078d44..228ab6ad 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/fold_6.py
+++ b/src/mednet/classify/config/data/tbpoc/fold_6.py
@@ -5,10 +5,10 @@
Database reference: [TB-POC-2018]_
-See :py:class:`mednet.libs.classification.config.data.tbpoc.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbpoc.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbpoc.datamodule import DataModule
+from mednet.classify.config.data.tbpoc.datamodule import DataModule
datamodule = DataModule("fold-6.json")
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold_7.py b/src/mednet/classify/config/data/tbpoc/fold_7.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/tbpoc/fold_7.py
rename to src/mednet/classify/config/data/tbpoc/fold_7.py
index 02d8cac0..a61268db 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/fold_7.py
+++ b/src/mednet/classify/config/data/tbpoc/fold_7.py
@@ -5,10 +5,10 @@
Database reference: [TB-POC-2018]_
-See :py:class:`mednet.libs.classification.config.data.tbpoc.datamodule.DataModule` for technical
-details.
+See :py:class:`mednet.classify.config.data.tbpoc.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.tbpoc.datamodule import DataModule
+from mednet.classify.config.data.tbpoc.datamodule import DataModule
datamodule = DataModule("fold-7.json")
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold_8.py b/src/mednet/classify/config/data/tbpoc/fold_8.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/tbpoc/fold_8.py
rename to src/mednet/classify/config/data/tbpoc/fold_8.py
index 4a19a705..7453ac83 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/fold_8.py
+++ b/src/mednet/classify/config/data/tbpoc/fold_8.py
@@ -5,10 +5,10 @@
Database reference: [TB-POC-2018]_
-See :py:class:`mednet.libs.classification.config.data.tbpoc.datamodule.DataModule` for technical
-details.
+See :py:class:`mednet.classify.config.data.tbpoc.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.tbpoc.datamodule import DataModule
+from mednet.classify.config.data.tbpoc.datamodule import DataModule
datamodule = DataModule("fold-8.json")
diff --git a/src/mednet/libs/classification/config/data/tbpoc/fold_9.py b/src/mednet/classify/config/data/tbpoc/fold_9.py
similarity index 60%
rename from src/mednet/libs/classification/config/data/tbpoc/fold_9.py
rename to src/mednet/classify/config/data/tbpoc/fold_9.py
index 358d305a..e4732bb7 100644
--- a/src/mednet/libs/classification/config/data/tbpoc/fold_9.py
+++ b/src/mednet/classify/config/data/tbpoc/fold_9.py
@@ -5,10 +5,10 @@
Database reference: [TB-POC-2018]_
-See :py:class:`mednet.libs.classification.config.data.tbpoc.datamodule.DataModule` for technical
-details.
+See :py:class:`mednet.classify.config.data.tbpoc.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.tbpoc.datamodule import DataModule
+from mednet.classify.config.data.tbpoc.datamodule import DataModule
datamodule = DataModule("fold-9.json")
diff --git a/src/mednet/libs/classification/config/data/visceral/__init__.py b/src/mednet/classify/config/data/tbx11k/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/data/visceral/__init__.py
rename to src/mednet/classify/config/data/tbx11k/__init__.py
diff --git a/src/mednet/libs/classification/config/data/tbx11k/datamodule.py b/src/mednet/classify/config/data/tbx11k/datamodule.py
similarity index 97%
rename from src/mednet/libs/classification/config/data/tbx11k/datamodule.py
rename to src/mednet/classify/config/data/tbx11k/datamodule.py
index f120a2af..94e9020e 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/datamodule.py
+++ b/src/mednet/classify/config/data/tbx11k/datamodule.py
@@ -10,16 +10,15 @@ import typing
import PIL.Image
import typing_extensions
-from mednet.libs.classification.data.typing import (
- ClassificationRawDataLoader as _ClassificationRawDataLoader,
-)
-from mednet.libs.classification.data.typing import Sample
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
from torch.utils.data._utils.collate import default_collate_fn_map
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import ClassificationRawDataLoader as _ClassificationRawDataLoader
+from ....data.typing import Sample
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -381,4 +380,5 @@ class DataModule(CachingDataModule):
raw_data_loader=ClassificationRawDataLoader(ignore_bboxes=ignore_bboxes),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-fold-0.json b/src/mednet/classify/config/data/tbx11k/v1-fold-0.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-fold-0.json
rename to src/mednet/classify/config/data/tbx11k/v1-fold-0.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-fold-1.json b/src/mednet/classify/config/data/tbx11k/v1-fold-1.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-fold-1.json
rename to src/mednet/classify/config/data/tbx11k/v1-fold-1.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-fold-2.json b/src/mednet/classify/config/data/tbx11k/v1-fold-2.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-fold-2.json
rename to src/mednet/classify/config/data/tbx11k/v1-fold-2.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-fold-3.json b/src/mednet/classify/config/data/tbx11k/v1-fold-3.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-fold-3.json
rename to src/mednet/classify/config/data/tbx11k/v1-fold-3.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-fold-4.json b/src/mednet/classify/config/data/tbx11k/v1-fold-4.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-fold-4.json
rename to src/mednet/classify/config/data/tbx11k/v1-fold-4.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-fold-5.json b/src/mednet/classify/config/data/tbx11k/v1-fold-5.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-fold-5.json
rename to src/mednet/classify/config/data/tbx11k/v1-fold-5.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-fold-6.json b/src/mednet/classify/config/data/tbx11k/v1-fold-6.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-fold-6.json
rename to src/mednet/classify/config/data/tbx11k/v1-fold-6.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-fold-7.json b/src/mednet/classify/config/data/tbx11k/v1-fold-7.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-fold-7.json
rename to src/mednet/classify/config/data/tbx11k/v1-fold-7.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-fold-8.json b/src/mednet/classify/config/data/tbx11k/v1-fold-8.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-fold-8.json
rename to src/mednet/classify/config/data/tbx11k/v1-fold-8.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-fold-9.json b/src/mednet/classify/config/data/tbx11k/v1-fold-9.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-fold-9.json
rename to src/mednet/classify/config/data/tbx11k/v1-fold-9.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1-healthy-vs-atb.json b/src/mednet/classify/config/data/tbx11k/v1-healthy-vs-atb.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v1-healthy-vs-atb.json
rename to src/mednet/classify/config/data/tbx11k/v1-healthy-vs-atb.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_0.py b/src/mednet/classify/config/data/tbx11k/v1_fold_0.py
similarity index 63%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_fold_0.py
rename to src/mednet/classify/config/data/tbx11k/v1_fold_0.py
index c3616561..ac09c68c 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_0.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_fold_0.py
@@ -6,10 +6,10 @@ cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-fold-0.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_1.py b/src/mednet/classify/config/data/tbx11k/v1_fold_1.py
similarity index 63%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_fold_1.py
rename to src/mednet/classify/config/data/tbx11k/v1_fold_1.py
index a430dfb7..b8b2be23 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_1.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_fold_1.py
@@ -6,10 +6,10 @@ cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-fold-1.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_2.py b/src/mednet/classify/config/data/tbx11k/v1_fold_2.py
similarity index 63%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_fold_2.py
rename to src/mednet/classify/config/data/tbx11k/v1_fold_2.py
index 9de38692..5e6b451f 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_2.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_fold_2.py
@@ -6,10 +6,10 @@ cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-fold-2.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_3.py b/src/mednet/classify/config/data/tbx11k/v1_fold_3.py
similarity index 63%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_fold_3.py
rename to src/mednet/classify/config/data/tbx11k/v1_fold_3.py
index 9e57ebd9..fa8f2fca 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_3.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_fold_3.py
@@ -6,10 +6,10 @@ cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-fold-3.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_4.py b/src/mednet/classify/config/data/tbx11k/v1_fold_4.py
similarity index 63%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_fold_4.py
rename to src/mednet/classify/config/data/tbx11k/v1_fold_4.py
index f6236f3b..68113aef 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_4.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_fold_4.py
@@ -6,10 +6,10 @@ cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-fold-4.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_5.py b/src/mednet/classify/config/data/tbx11k/v1_fold_5.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_fold_5.py
rename to src/mednet/classify/config/data/tbx11k/v1_fold_5.py
index 404195d3..4eda5029 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_5.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_fold_5.py
@@ -6,10 +6,10 @@ cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
-details.
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-fold-5.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_6.py b/src/mednet/classify/config/data/tbx11k/v1_fold_6.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_fold_6.py
rename to src/mednet/classify/config/data/tbx11k/v1_fold_6.py
index 6edf3017..3d044552 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_6.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_fold_6.py
@@ -6,10 +6,10 @@ cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
-details.
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-fold-6.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_7.py b/src/mednet/classify/config/data/tbx11k/v1_fold_7.py
similarity index 63%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_fold_7.py
rename to src/mednet/classify/config/data/tbx11k/v1_fold_7.py
index 71f989ea..7ae445f3 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_7.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_fold_7.py
@@ -6,10 +6,10 @@ cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-fold-7.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_8.py b/src/mednet/classify/config/data/tbx11k/v1_fold_8.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_fold_8.py
rename to src/mednet/classify/config/data/tbx11k/v1_fold_8.py
index 124b6403..1d35ffa1 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_8.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_fold_8.py
@@ -6,10 +6,10 @@ cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
-details.
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-fold-8.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_9.py b/src/mednet/classify/config/data/tbx11k/v1_fold_9.py
similarity index 63%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_fold_9.py
rename to src/mednet/classify/config/data/tbx11k/v1_fold_9.py
index 54f80790..3dda7097 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_fold_9.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_fold_9.py
@@ -6,10 +6,10 @@ cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-fold-9.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v1_healthy_vs_atb.py b/src/mednet/classify/config/data/tbx11k/v1_healthy_vs_atb.py
similarity index 79%
rename from src/mednet/libs/classification/config/data/tbx11k/v1_healthy_vs_atb.py
rename to src/mednet/classify/config/data/tbx11k/v1_healthy_vs_atb.py
index f66852b9..253c9ec3 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v1_healthy_vs_atb.py
+++ b/src/mednet/classify/config/data/tbx11k/v1_healthy_vs_atb.py
@@ -27,10 +27,10 @@ Split v1 contains healthy subjects against active TB cases (total samples =
- Active TB only: 157
- Total: 957
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v1-healthy-vs-atb.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-fold-0.json b/src/mednet/classify/config/data/tbx11k/v2-fold-0.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-fold-0.json
rename to src/mednet/classify/config/data/tbx11k/v2-fold-0.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-fold-1.json b/src/mednet/classify/config/data/tbx11k/v2-fold-1.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-fold-1.json
rename to src/mednet/classify/config/data/tbx11k/v2-fold-1.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-fold-2.json b/src/mednet/classify/config/data/tbx11k/v2-fold-2.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-fold-2.json
rename to src/mednet/classify/config/data/tbx11k/v2-fold-2.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-fold-3.json b/src/mednet/classify/config/data/tbx11k/v2-fold-3.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-fold-3.json
rename to src/mednet/classify/config/data/tbx11k/v2-fold-3.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-fold-4.json b/src/mednet/classify/config/data/tbx11k/v2-fold-4.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-fold-4.json
rename to src/mednet/classify/config/data/tbx11k/v2-fold-4.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-fold-5.json b/src/mednet/classify/config/data/tbx11k/v2-fold-5.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-fold-5.json
rename to src/mednet/classify/config/data/tbx11k/v2-fold-5.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-fold-6.json b/src/mednet/classify/config/data/tbx11k/v2-fold-6.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-fold-6.json
rename to src/mednet/classify/config/data/tbx11k/v2-fold-6.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-fold-7.json b/src/mednet/classify/config/data/tbx11k/v2-fold-7.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-fold-7.json
rename to src/mednet/classify/config/data/tbx11k/v2-fold-7.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-fold-8.json b/src/mednet/classify/config/data/tbx11k/v2-fold-8.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-fold-8.json
rename to src/mednet/classify/config/data/tbx11k/v2-fold-8.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-fold-9.json b/src/mednet/classify/config/data/tbx11k/v2-fold-9.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-fold-9.json
rename to src/mednet/classify/config/data/tbx11k/v2-fold-9.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2-others-vs-atb.json b/src/mednet/classify/config/data/tbx11k/v2-others-vs-atb.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/tbx11k/v2-others-vs-atb.json
rename to src/mednet/classify/config/data/tbx11k/v2-others-vs-atb.json
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_0.py b/src/mednet/classify/config/data/tbx11k/v2_fold_0.py
similarity index 65%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_fold_0.py
rename to src/mednet/classify/config/data/tbx11k/v2_fold_0.py
index 230727a8..205b1043 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_0.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_fold_0.py
@@ -6,10 +6,10 @@ TB vs. active TB cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-fold-0.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_1.py b/src/mednet/classify/config/data/tbx11k/v2_fold_1.py
similarity index 65%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_fold_1.py
rename to src/mednet/classify/config/data/tbx11k/v2_fold_1.py
index e35d4be1..19cba846 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_1.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_fold_1.py
@@ -6,10 +6,10 @@ TB vs. active TB cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-fold-1.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_2.py b/src/mednet/classify/config/data/tbx11k/v2_fold_2.py
similarity index 65%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_fold_2.py
rename to src/mednet/classify/config/data/tbx11k/v2_fold_2.py
index 49183079..11f12bd6 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_2.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_fold_2.py
@@ -6,10 +6,10 @@ TB vs. active TB cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-fold-2.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_3.py b/src/mednet/classify/config/data/tbx11k/v2_fold_3.py
similarity index 65%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_fold_3.py
rename to src/mednet/classify/config/data/tbx11k/v2_fold_3.py
index fc261fcc..59876cd1 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_3.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_fold_3.py
@@ -6,10 +6,10 @@ TB vs. active TB cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-fold-3.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_4.py b/src/mednet/classify/config/data/tbx11k/v2_fold_4.py
similarity index 65%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_fold_4.py
rename to src/mednet/classify/config/data/tbx11k/v2_fold_4.py
index 7d743ba7..cb7265fc 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_4.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_fold_4.py
@@ -6,10 +6,10 @@ TB vs. active TB cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-fold-4.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_5.py b/src/mednet/classify/config/data/tbx11k/v2_fold_5.py
similarity index 65%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_fold_5.py
rename to src/mednet/classify/config/data/tbx11k/v2_fold_5.py
index 0b72cfd7..346661d5 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_5.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_fold_5.py
@@ -6,10 +6,10 @@ TB vs. active TB cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-fold-5.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_6.py b/src/mednet/classify/config/data/tbx11k/v2_fold_6.py
similarity index 65%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_fold_6.py
rename to src/mednet/classify/config/data/tbx11k/v2_fold_6.py
index d530bd58..47fb33d7 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_6.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_fold_6.py
@@ -6,10 +6,10 @@ TB vs. active TB cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-fold-6.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_7.py b/src/mednet/classify/config/data/tbx11k/v2_fold_7.py
similarity index 65%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_fold_7.py
rename to src/mednet/classify/config/data/tbx11k/v2_fold_7.py
index f5c6b526..c7ab755f 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_7.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_fold_7.py
@@ -6,10 +6,10 @@ TB vs. active TB cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-fold-7.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_8.py b/src/mednet/classify/config/data/tbx11k/v2_fold_8.py
similarity index 65%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_fold_8.py
rename to src/mednet/classify/config/data/tbx11k/v2_fold_8.py
index 2ea12f81..7ade1e0c 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_8.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_fold_8.py
@@ -6,10 +6,10 @@ TB vs. active TB cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-fold-8.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_9.py b/src/mednet/classify/config/data/tbx11k/v2_fold_9.py
similarity index 63%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_fold_9.py
rename to src/mednet/classify/config/data/tbx11k/v2_fold_9.py
index 8d695388..3ebe1af9 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_fold_9.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_fold_9.py
@@ -6,10 +6,10 @@ TB vs. active TB cases).
Database reference: [TBX11K-2020]_
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
-details.
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for
+technical details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-fold-9.json")
diff --git a/src/mednet/libs/classification/config/data/tbx11k/v2_others_vs_atb.py b/src/mednet/classify/config/data/tbx11k/v2_others_vs_atb.py
similarity index 81%
rename from src/mednet/libs/classification/config/data/tbx11k/v2_others_vs_atb.py
rename to src/mednet/classify/config/data/tbx11k/v2_others_vs_atb.py
index cc330216..912d9877 100644
--- a/src/mednet/libs/classification/config/data/tbx11k/v2_others_vs_atb.py
+++ b/src/mednet/classify/config/data/tbx11k/v2_others_vs_atb.py
@@ -27,10 +27,10 @@ active TB cases (total samples = 8369):
- Active TB only: 157
- Total: 1793
-See :py:class:`mednet.libs.classification.config.data.tbx11k.datamodule.DataModule` for technical
+See :py:class:`mednet.classify.config.data.tbx11k.datamodule.DataModule` for technical
details.
"""
-from mednet.libs.classification.config.data.tbx11k.datamodule import DataModule
+from mednet.classify.config.data.tbx11k.datamodule import DataModule
datamodule = DataModule("v2-others-vs-atb.json")
diff --git a/src/mednet/libs/classification/config/models/__init__.py b/src/mednet/classify/config/data/visceral/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/config/models/__init__.py
rename to src/mednet/classify/config/data/visceral/__init__.py
diff --git a/src/mednet/libs/classification/config/data/visceral/datamodule.py b/src/mednet/classify/config/data/visceral/datamodule.py
similarity index 90%
rename from src/mednet/libs/classification/config/data/visceral/datamodule.py
rename to src/mednet/classify/config/data/visceral/datamodule.py
index 1b5b9664..456ec186 100644
--- a/src/mednet/libs/classification/config/data/visceral/datamodule.py
+++ b/src/mednet/classify/config/data/visceral/datamodule.py
@@ -12,13 +12,12 @@ import pathlib
import typing
import torchio as tio
-from mednet.libs.classification.data.typing import (
- ClassificationRawDataLoader as _ClassificationRawDataLoader,
-)
-from mednet.libs.classification.data.typing import Sample
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
+
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import ClassificationRawDataLoader as _ClassificationRawDataLoader
+from ....data.typing import Sample
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
@@ -117,4 +116,5 @@ class DataModule(CachingDataModule):
raw_data_loader=ClassificationRawDataLoader(),
database_name=__package__.split(".")[-1],
split_name=pathlib.Path(split_filename).stem,
+ task="classification",
)
diff --git a/src/mednet/libs/classification/config/data/visceral/default.json b/src/mednet/classify/config/data/visceral/default.json
similarity index 100%
rename from src/mednet/libs/classification/config/data/visceral/default.json
rename to src/mednet/classify/config/data/visceral/default.json
diff --git a/src/mednet/libs/classification/config/data/visceral/default.py b/src/mednet/classify/config/data/visceral/default.py
similarity index 61%
rename from src/mednet/libs/classification/config/data/visceral/default.py
rename to src/mednet/classify/config/data/visceral/default.py
index 5dc0bbd1..b657c94a 100644
--- a/src/mednet/libs/classification/config/data/visceral/default.py
+++ b/src/mednet/classify/config/data/visceral/default.py
@@ -4,10 +4,10 @@
"""VISCERAL dataset for 3D organ classification.
See
-:py:class:`mednet.libs.classification.config.data.visceral.datamodule.DataModule`
+:py:class:`mednet.classify.config.data.visceral.datamodule.DataModule`
for technical details.
"""
-from mednet.libs.classification.config.data.visceral.datamodule import DataModule
+from mednet.classify.config.data.visceral.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/classification/data/__init__.py b/src/mednet/classify/config/models/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/data/__init__.py
rename to src/mednet/classify/config/models/__init__.py
diff --git a/src/mednet/libs/classification/config/models/alexnet.py b/src/mednet/classify/config/models/alexnet.py
similarity index 70%
rename from src/mednet/libs/classification/config/models/alexnet.py
rename to src/mednet/classify/config/models/alexnet.py
index 1ad84eaf..24981517 100644
--- a/src/mednet/libs/classification/config/models/alexnet.py
+++ b/src/mednet/classify/config/models/alexnet.py
@@ -8,20 +8,21 @@ This configuration contains a version of AlexNet_ (c.f. `TorchVision's page
1).
"""
-import mednet.libs.classification.models.alexnet
-import mednet.libs.common.models.transforms
import torch.nn
import torch.optim
import torchvision.transforms
-model = mednet.libs.classification.models.alexnet.Alexnet(
+import mednet.classify.models.alexnet
+import mednet.models.transforms
+
+model = mednet.classify.models.alexnet.Alexnet(
loss_type=torch.nn.BCEWithLogitsLoss,
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.001),
pretrained=False,
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
)
diff --git a/src/mednet/libs/classification/config/models/alexnet_pretrained.py b/src/mednet/classify/config/models/alexnet_pretrained.py
similarity index 72%
rename from src/mednet/libs/classification/config/models/alexnet_pretrained.py
rename to src/mednet/classify/config/models/alexnet_pretrained.py
index 3ca94217..9a27ac10 100644
--- a/src/mednet/libs/classification/config/models/alexnet_pretrained.py
+++ b/src/mednet/classify/config/models/alexnet_pretrained.py
@@ -10,20 +10,21 @@ page <alexnet-pytorch_>`_), modified for a variable number of outputs
N.B.: The output layer is **always** initialized from scratch.
"""
-import mednet.libs.classification.models.alexnet
-import mednet.libs.common.models.transforms
import torch.nn
import torch.optim
import torchvision.transforms
-model = mednet.libs.classification.models.alexnet.Alexnet(
+import mednet.classify.models.alexnet
+import mednet.models.transforms
+
+model = mednet.classify.models.alexnet.Alexnet(
loss_type=torch.nn.BCEWithLogitsLoss,
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.0001),
pretrained=True,
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
)
diff --git a/src/mednet/libs/classification/config/models/cnn3d.py b/src/mednet/classify/config/models/cnn3d.py
similarity index 86%
rename from src/mednet/libs/classification/config/models/cnn3d.py
rename to src/mednet/classify/config/models/cnn3d.py
index 2c956834..f4fa2e7d 100644
--- a/src/mednet/libs/classification/config/models/cnn3d.py
+++ b/src/mednet/classify/config/models/cnn3d.py
@@ -3,10 +3,11 @@
# SPDX-License-Identifier: GPL-3.0-or-later
"""Simple CNN for 3D image classification, to be trained from scratch."""
-from mednet.libs.classification.models.cnn3d import Conv3DNet
from torch.nn import BCEWithLogitsLoss
from torch.optim import Adam
+from mednet.classify.models.cnn3d import Conv3DNet
+
model = Conv3DNet(
loss_type=BCEWithLogitsLoss,
optimizer_type=Adam,
diff --git a/src/mednet/libs/classification/config/models/densenet.py b/src/mednet/classify/config/models/densenet.py
similarity index 70%
rename from src/mednet/libs/classification/config/models/densenet.py
rename to src/mednet/classify/config/models/densenet.py
index 5bdce923..9ddf1b24 100644
--- a/src/mednet/libs/classification/config/models/densenet.py
+++ b/src/mednet/classify/config/models/densenet.py
@@ -8,21 +8,22 @@ page <densenet_pytorch_>`), modified for a variable number of outputs
(defaults to 1).
"""
-import mednet.libs.classification.models.densenet
-import mednet.libs.common.models.transforms
import torch.nn
import torch.optim
import torchvision.transforms
-model = mednet.libs.classification.models.densenet.Densenet(
+import mednet.classify.models.densenet
+import mednet.models.transforms
+
+model = mednet.classify.models.densenet.Densenet(
loss_type=torch.nn.BCEWithLogitsLoss,
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.0001),
pretrained=False,
dropout=0.1,
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
)
diff --git a/src/mednet/libs/classification/config/models/densenet_pretrained.py b/src/mednet/classify/config/models/densenet_pretrained.py
similarity index 73%
rename from src/mednet/libs/classification/config/models/densenet_pretrained.py
rename to src/mednet/classify/config/models/densenet_pretrained.py
index 95a9663d..070aaae4 100644
--- a/src/mednet/libs/classification/config/models/densenet_pretrained.py
+++ b/src/mednet/classify/config/models/densenet_pretrained.py
@@ -10,21 +10,22 @@ page <alexnet_pytorch_>`), modified for a variable number of outputs
N.B.: The output layer is **always** initialized from scratch.
"""
-import mednet.libs.classification.models.densenet
-import mednet.libs.common.models.transforms
import torch.nn
import torch.optim
import torchvision.transforms
-model = mednet.libs.classification.models.densenet.Densenet(
+import mednet.classify.models.densenet
+import mednet.models.transforms
+
+model = mednet.classify.models.densenet.Densenet(
loss_type=torch.nn.BCEWithLogitsLoss,
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.0001),
pretrained=True,
dropout=0.1,
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
)
diff --git a/src/mednet/libs/classification/config/models/densenet_rs.py b/src/mednet/classify/config/models/densenet_rs.py
similarity index 75%
rename from src/mednet/libs/classification/config/models/densenet_rs.py
rename to src/mednet/classify/config/models/densenet_rs.py
index 002b3f5b..0a9476f3 100644
--- a/src/mednet/libs/classification/config/models/densenet_rs.py
+++ b/src/mednet/classify/config/models/densenet_rs.py
@@ -9,13 +9,14 @@ page <densenet_pytorch_>`), modified to have exactly 14 outputs
weights from scratch for radiological sign detection.
"""
-import mednet.libs.classification.models.densenet
-import mednet.libs.common.models.transforms
import torch.nn
import torch.optim
import torchvision.transforms
-model = mednet.libs.classification.models.densenet.Densenet(
+import mednet.classify.models.densenet
+import mednet.models.transforms
+
+model = mednet.classify.models.densenet.Densenet(
loss_type=torch.nn.BCEWithLogitsLoss,
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.0001),
@@ -23,8 +24,8 @@ model = mednet.libs.classification.models.densenet.Densenet(
dropout=0.1,
num_classes=14, # number of classes in NIH CXR-14
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
)
diff --git a/src/mednet/libs/classification/config/models/logistic_regression.py b/src/mednet/classify/config/models/logistic_regression.py
similarity index 82%
rename from src/mednet/libs/classification/config/models/logistic_regression.py
rename to src/mednet/classify/config/models/logistic_regression.py
index 69178027..9e8a58d4 100644
--- a/src/mednet/libs/classification/config/models/logistic_regression.py
+++ b/src/mednet/classify/config/models/logistic_regression.py
@@ -8,8 +8,6 @@ the output of :py:mod:`.densenet_rs` and be trained for binary classification
(e.g. for active TB detection).
"""
-from mednet.libs.classification.models.logistic_regression import (
- LogisticRegression,
-)
+from mednet.classify.models.logistic_regression import LogisticRegression
model = LogisticRegression(input_size=14)
diff --git a/src/mednet/libs/classification/config/models/mlp.py b/src/mednet/classify/config/models/mlp.py
similarity index 84%
rename from src/mednet/libs/classification/config/models/mlp.py
rename to src/mednet/classify/config/models/mlp.py
index 51a28c17..6cfe08b1 100644
--- a/src/mednet/libs/classification/config/models/mlp.py
+++ b/src/mednet/classify/config/models/mlp.py
@@ -8,6 +8,6 @@ output (e.g. to predict active TB presence from radiological finding
estimates).
"""
-from mednet.libs.classification.models.mlp import MultiLayerPerceptron
+from mednet.classify.models.mlp import MultiLayerPerceptron
model = MultiLayerPerceptron()
diff --git a/src/mednet/libs/classification/config/models/pasa.py b/src/mednet/classify/config/models/pasa.py
similarity index 78%
rename from src/mednet/libs/classification/config/models/pasa.py
rename to src/mednet/classify/config/models/pasa.py
index 41c96a59..3f28074b 100644
--- a/src/mednet/libs/classification/config/models/pasa.py
+++ b/src/mednet/classify/config/models/pasa.py
@@ -10,19 +10,20 @@ Screening and Visualization".
Reference: [PASA-2019]_
"""
-import mednet.libs.classification.models.pasa
-import mednet.libs.common.models.transforms
import torch.nn
import torch.optim
import torchvision.transforms
-model = mednet.libs.classification.models.pasa.Pasa(
+import mednet.classify.models.pasa
+import mednet.models.transforms
+
+model = mednet.classify.models.pasa.Pasa(
loss_type=torch.nn.BCEWithLogitsLoss,
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=8e-5),
model_transforms=[
torchvision.transforms.Grayscale(),
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
],
augmentation_transforms=[],
diff --git a/src/mednet/libs/classification/engine/__init__.py b/src/mednet/classify/data/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/engine/__init__.py
rename to src/mednet/classify/data/__init__.py
diff --git a/src/mednet/libs/classification/data/typing.py b/src/mednet/classify/data/typing.py
similarity index 77%
rename from src/mednet/libs/classification/data/typing.py
rename to src/mednet/classify/data/typing.py
index 3a29c2bf..268c6fb6 100644
--- a/src/mednet/libs/classification/data/typing.py
+++ b/src/mednet/classify/data/typing.py
@@ -1,7 +1,14 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+"""Define specialized data typing for classification tasks."""
+
import typing
import torch
-from mednet.libs.common.data.typing import RawDataLoader
+
+from ...data.typing import RawDataLoader
Sample: typing.TypeAlias = tuple[torch.Tensor, typing.Mapping[str, typing.Any]]
@@ -12,12 +19,12 @@ class ClassificationRawDataLoader(RawDataLoader):
def __init__(self):
super().__init__()
- def sample(self, _: tuple[str, int, typing.Any | None]) -> Sample:
+ def sample(self, sample: tuple[str, int, typing.Any | None]) -> Sample:
"""Load whole samples from media.
Parameters
----------
- _
+ sample
Information about the sample to load. Implementation dependent.
"""
diff --git a/src/mednet/libs/classification/engine/saliency/__init__.py b/src/mednet/classify/engine/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/engine/saliency/__init__.py
rename to src/mednet/classify/engine/__init__.py
diff --git a/src/mednet/libs/classification/engine/evaluator.py b/src/mednet/classify/engine/evaluator.py
similarity index 98%
rename from src/mednet/libs/classification/engine/evaluator.py
rename to src/mednet/classify/engine/evaluator.py
index d0af84bc..e3d7a4c8 100644
--- a/src/mednet/libs/classification/engine/evaluator.py
+++ b/src/mednet/classify/engine/evaluator.py
@@ -184,12 +184,12 @@ def run_binary(
y_predictions,
pos_label=pos_label,
),
- f1_score=sklearn.metrics.f1_score(
+ f1=sklearn.metrics.f1_score(
y_labels,
y_predictions,
pos_label=pos_label,
),
- average_precision_score=sklearn.metrics.average_precision_score(
+ average_precision=sklearn.metrics.average_precision_score(
y_labels,
y_scores,
pos_label=pos_label,
@@ -199,7 +199,7 @@ def run_binary(
y_predictions,
pos_label=neg_label,
),
- auc_score=sklearn.metrics.roc_auc_score(
+ roc_auc=sklearn.metrics.roc_auc_score(
y_labels,
y_scores,
),
diff --git a/src/mednet/libs/classification/engine/predictor.py b/src/mednet/classify/engine/predictor.py
similarity index 99%
rename from src/mednet/libs/classification/engine/predictor.py
rename to src/mednet/classify/engine/predictor.py
index 752070f6..683bca17 100644
--- a/src/mednet/libs/classification/engine/predictor.py
+++ b/src/mednet/classify/engine/predictor.py
@@ -7,8 +7,8 @@ import typing
import lightning.pytorch
import torch.utils.data
-from mednet.libs.common.engine.device import DeviceManager
+from ...engine.device import DeviceManager
from ..models.typing import (
BinaryPrediction,
BinaryPredictionSplit,
diff --git a/src/mednet/libs/classification/models/__init__.py b/src/mednet/classify/engine/saliency/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/models/__init__.py
rename to src/mednet/classify/engine/saliency/__init__.py
diff --git a/src/mednet/libs/classification/engine/saliency/completeness.py b/src/mednet/classify/engine/saliency/completeness.py
similarity index 99%
rename from src/mednet/libs/classification/engine/saliency/completeness.py
rename to src/mednet/classify/engine/saliency/completeness.py
index f632afee..8c8aba84 100644
--- a/src/mednet/libs/classification/engine/saliency/completeness.py
+++ b/src/mednet/classify/engine/saliency/completeness.py
@@ -11,14 +11,14 @@ import lightning.pytorch
import numpy as np
import torch
import tqdm
-from mednet.libs.classification.data.typing import Sample
-from mednet.libs.common.engine.device import DeviceManager
from pytorch_grad_cam.metrics.road import (
ROADLeastRelevantFirstAverage,
ROADMostRelevantFirstAverage,
)
from pytorch_grad_cam.utils.model_targets import ClassifierOutputTarget
+from ....engine.device import DeviceManager
+from ...data.typing import Sample
from ...models.typing import SaliencyMapAlgorithm
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/classification/engine/saliency/evaluator.py b/src/mednet/classify/engine/saliency/evaluator.py
similarity index 100%
rename from src/mednet/libs/classification/engine/saliency/evaluator.py
rename to src/mednet/classify/engine/saliency/evaluator.py
diff --git a/src/mednet/libs/classification/engine/saliency/generator.py b/src/mednet/classify/engine/saliency/generator.py
similarity index 99%
rename from src/mednet/libs/classification/engine/saliency/generator.py
rename to src/mednet/classify/engine/saliency/generator.py
index 5fc43415..7a38be9f 100644
--- a/src/mednet/libs/classification/engine/saliency/generator.py
+++ b/src/mednet/classify/engine/saliency/generator.py
@@ -11,8 +11,8 @@ import numpy
import torch
import torch.nn
import tqdm
-from mednet.libs.common.engine.device import DeviceManager
+from ....engine.device import DeviceManager
from ...models.typing import SaliencyMapAlgorithm
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/classification/engine/saliency/interpretability.py b/src/mednet/classify/engine/saliency/interpretability.py
similarity index 100%
rename from src/mednet/libs/classification/engine/saliency/interpretability.py
rename to src/mednet/classify/engine/saliency/interpretability.py
diff --git a/src/mednet/libs/classification/engine/saliency/viewer.py b/src/mednet/classify/engine/saliency/viewer.py
similarity index 100%
rename from src/mednet/libs/classification/engine/saliency/viewer.py
rename to src/mednet/classify/engine/saliency/viewer.py
diff --git a/src/mednet/libs/classification/scripts/__init__.py b/src/mednet/classify/models/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/scripts/__init__.py
rename to src/mednet/classify/models/__init__.py
diff --git a/src/mednet/libs/classification/models/alexnet.py b/src/mednet/classify/models/alexnet.py
similarity index 98%
rename from src/mednet/libs/classification/models/alexnet.py
rename to src/mednet/classify/models/alexnet.py
index 320e850c..1b34b64a 100644
--- a/src/mednet/libs/classification/models/alexnet.py
+++ b/src/mednet/classify/models/alexnet.py
@@ -10,8 +10,8 @@ import torch.nn
import torch.optim.optimizer
import torch.utils.data
import torchvision.models as models
-from mednet.libs.common.data.typing import TransformSequence
+from ...data.typing import TransformSequence
from .classification_model import ClassificationModel
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/classification/models/classification_model.py b/src/mednet/classify/models/classification_model.py
similarity index 97%
rename from src/mednet/libs/classification/models/classification_model.py
rename to src/mednet/classify/models/classification_model.py
index 51f6fa18..3a622c39 100644
--- a/src/mednet/libs/classification/models/classification_model.py
+++ b/src/mednet/classify/models/classification_model.py
@@ -9,8 +9,9 @@ import torch
import torch.nn
import torch.optim.optimizer
import torch.utils.data
-from mednet.libs.common.data.typing import TransformSequence
-from mednet.libs.common.models.model import Model
+
+from ...data.typing import TransformSequence
+from ...models.model import Model
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/classification/models/cnn3d.py b/src/mednet/classify/models/cnn3d.py
similarity index 99%
rename from src/mednet/libs/classification/models/cnn3d.py
rename to src/mednet/classify/models/cnn3d.py
index 64bf4893..5cf54d83 100644
--- a/src/mednet/libs/classification/models/cnn3d.py
+++ b/src/mednet/classify/models/cnn3d.py
@@ -11,7 +11,7 @@ import torch.nn.functional as F # noqa: N812
import torch.optim.optimizer
import torch.utils.data
-from ...common.data.typing import TransformSequence
+from ...data.typing import TransformSequence
from ..models.classification_model import ClassificationModel
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/classification/models/densenet.py b/src/mednet/classify/models/densenet.py
similarity index 98%
rename from src/mednet/libs/classification/models/densenet.py
rename to src/mednet/classify/models/densenet.py
index e2e92793..7caa6e84 100644
--- a/src/mednet/libs/classification/models/densenet.py
+++ b/src/mednet/classify/models/densenet.py
@@ -10,8 +10,8 @@ import torch.nn
import torch.optim.optimizer
import torch.utils.data
import torchvision.models as models
-from mednet.libs.common.data.typing import TransformSequence
+from ...data.typing import TransformSequence
from .classification_model import ClassificationModel
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/classification/models/logistic_regression.py b/src/mednet/classify/models/logistic_regression.py
similarity index 100%
rename from src/mednet/libs/classification/models/logistic_regression.py
rename to src/mednet/classify/models/logistic_regression.py
diff --git a/src/mednet/libs/classification/models/loss_weights.py b/src/mednet/classify/models/loss_weights.py
similarity index 97%
rename from src/mednet/libs/classification/models/loss_weights.py
rename to src/mednet/classify/models/loss_weights.py
index e9de5375..ab19a9c5 100644
--- a/src/mednet/libs/classification/models/loss_weights.py
+++ b/src/mednet/classify/models/loss_weights.py
@@ -6,7 +6,8 @@ import logging
import torch
import torch.utils.data
-from mednet.libs.common.data.typing import DataLoader
+
+from ...data.typing import DataLoader
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/classification/models/mlp.py b/src/mednet/classify/models/mlp.py
similarity index 100%
rename from src/mednet/libs/classification/models/mlp.py
rename to src/mednet/classify/models/mlp.py
diff --git a/src/mednet/libs/classification/models/normalizer.py b/src/mednet/classify/models/normalizer.py
similarity index 100%
rename from src/mednet/libs/classification/models/normalizer.py
rename to src/mednet/classify/models/normalizer.py
diff --git a/src/mednet/libs/classification/models/pasa.py b/src/mednet/classify/models/pasa.py
similarity index 99%
rename from src/mednet/libs/classification/models/pasa.py
rename to src/mednet/classify/models/pasa.py
index 6f0c7c75..eb28b9a8 100644
--- a/src/mednet/libs/classification/models/pasa.py
+++ b/src/mednet/classify/models/pasa.py
@@ -10,8 +10,8 @@ import torch.nn
import torch.nn.functional as F # noqa: N812
import torch.optim.optimizer
import torch.utils.data
-from mednet.libs.common.data.typing import TransformSequence
+from ...data.typing import TransformSequence
from .classification_model import ClassificationModel
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/classification/models/typing.py b/src/mednet/classify/models/typing.py
similarity index 100%
rename from src/mednet/libs/classification/models/typing.py
rename to src/mednet/classify/models/typing.py
diff --git a/src/mednet/libs/classification/scripts/saliency/__init__.py b/src/mednet/classify/scripts/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/scripts/saliency/__init__.py
rename to src/mednet/classify/scripts/__init__.py
diff --git a/src/mednet/classify/scripts/cli.py b/src/mednet/classify/scripts/cli.py
new file mode 100644
index 00000000..b127bc77
--- /dev/null
+++ b/src/mednet/classify/scripts/cli.py
@@ -0,0 +1,44 @@
+# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import importlib
+
+import click
+from clapper.click import AliasedGroup
+
+
+@click.group(
+ cls=AliasedGroup,
+ context_settings=dict(help_option_names=["-?", "-h", "--help"]),
+)
+def classify():
+ """Image classification specialized commands."""
+ pass
+
+
+def _add_command(cli, module, obj):
+ cli.add_command(
+ getattr(importlib.import_module("." + module, package=__name__), obj)
+ )
+
+
+_add_command(classify, ".evaluate", "evaluate")
+
+
+@click.group(
+ cls=AliasedGroup,
+ context_settings=dict(help_option_names=["-?", "-h", "--help"]),
+)
+def saliency():
+ """Generate, evaluate and view saliency maps."""
+ pass
+
+
+classify.add_command(saliency)
+
+_add_command(saliency, ".saliency.generate", "generate")
+_add_command(saliency, ".saliency.completeness", "completeness")
+_add_command(saliency, ".saliency.interpretability", "interpretability")
+_add_command(saliency, ".saliency.evaluate", "evaluate")
+_add_command(saliency, ".saliency.view", "view")
diff --git a/src/mednet/libs/classification/scripts/evaluate.py b/src/mednet/classify/scripts/evaluate.py
similarity index 94%
rename from src/mednet/libs/classification/scripts/evaluate.py
rename to src/mednet/classify/scripts/evaluate.py
index 45bf0ae6..6770323f 100644
--- a/src/mednet/libs/classification/scripts/evaluate.py
+++ b/src/mednet/classify/scripts/evaluate.py
@@ -7,7 +7,8 @@ import pathlib
import click
from clapper.click import ResourceOption, verbosity_option
from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
+
+from ...scripts.click import ConfigCommand
# avoids X11/graphical desktop requirement when creating plots
__import__("matplotlib").use("agg")
@@ -16,7 +17,7 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
@click.command(
- entry_point_group="mednet.libs.classification.config",
+ entry_point_group="mednet.config",
cls=ConfigCommand,
epilog="""Examples:
@@ -24,13 +25,13 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
.. code:: sh
- mednet classification evaluate -vv --predictions=path/to/predictions.json
+ mednet classify evaluate -vv --predictions=path/to/predictions.json
2. Run evaluation on an existing prediction output, tune threshold a priori on the `validation` set:
.. code:: sh
- mednet classification evaluate -vv --predictions=path/to/predictions.json --threshold=validation
+ mednet classify evaluate -vv --predictions=path/to/predictions.json --threshold=validation
""",
)
@click.option(
@@ -115,11 +116,11 @@ def evaluate(
import typing
import matplotlib.backends.backend_pdf
- from mednet.libs.common.scripts.utils import (
+
+ from ...scripts.utils import (
save_json_metadata,
save_json_with_backup,
)
-
from ..engine.evaluator import (
make_plots,
make_table,
diff --git a/src/mednet/libs/classification/utils/__init__.py b/src/mednet/classify/scripts/saliency/__init__.py
similarity index 100%
rename from src/mednet/libs/classification/utils/__init__.py
rename to src/mednet/classify/scripts/saliency/__init__.py
diff --git a/src/mednet/libs/classification/scripts/saliency/completeness.py b/src/mednet/classify/scripts/saliency/completeness.py
similarity index 92%
rename from src/mednet/libs/classification/scripts/saliency/completeness.py
rename to src/mednet/classify/scripts/saliency/completeness.py
index 7dcef916..80884872 100644
--- a/src/mednet/libs/classification/scripts/saliency/completeness.py
+++ b/src/mednet/classify/scripts/saliency/completeness.py
@@ -8,15 +8,15 @@ import typing
import click
from clapper.click import ResourceOption, verbosity_option
from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
+from ....scripts.click import ConfigCommand
from ...models.typing import SaliencyMapAlgorithm
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
@click.command(
- entry_point_group="mednet.libs.classification.config",
+ entry_point_group="mednet.config",
cls=ConfigCommand,
epilog="""Examples:
@@ -201,17 +201,12 @@ def completeness(
This application is relatively slow when processing a large DataModule
with many (positive) samples.
"""
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.scripts.predict import setup_datamodule
- from mednet.libs.common.scripts.utils import (
- save_json_metadata,
- save_json_with_backup,
- )
- from mednet.libs.common.utils.checkpointer import (
- get_checkpoint_to_run_inference,
- )
-
+ from ....engine.device import DeviceManager
+ from ....engine.trainer import validate_model_datamodule
+ from ....scripts.utils import save_json_metadata, save_json_with_backup
+ from ....utils.checkpointer import get_checkpoint_to_run_inference
from ...engine.saliency.completeness import run
+ from ...models.classification_model import ClassificationModel
if device in ("cuda", "mps") and (parallel == 0 or parallel > 1):
raise RuntimeError(
@@ -222,10 +217,17 @@ def completeness(
f"one, or disable multiprocessing entirely (ie. set it to -1).",
)
+ validate_model_datamodule(model, datamodule)
+ assert isinstance(model, ClassificationModel)
+
device_manager = DeviceManager(device)
datamodule.cache_samples = cache_samples
- setup_datamodule(datamodule, model, 1, parallel)
+ datamodule.model_transforms = list(model.model_transforms)
+ datamodule.batch_size = 1
+ datamodule.parallel = parallel
+ datamodule.prepare_data()
+ datamodule.setup(stage="predict")
if weight.is_dir():
weight = get_checkpoint_to_run_inference(weight)
diff --git a/src/mednet/libs/classification/scripts/saliency/evaluate.py b/src/mednet/classify/scripts/saliency/evaluate.py
similarity index 96%
rename from src/mednet/libs/classification/scripts/saliency/evaluate.py
rename to src/mednet/classify/scripts/saliency/evaluate.py
index 035d9b0e..067be4af 100644
--- a/src/mednet/libs/classification/scripts/saliency/evaluate.py
+++ b/src/mednet/classify/scripts/saliency/evaluate.py
@@ -8,8 +8,8 @@ import typing
import click
from clapper.click import ResourceOption, verbosity_option
from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
+from ....scripts.click import ConfigCommand
from ...models.typing import SaliencyMapAlgorithm
# avoids X11/graphical desktop requirement when creating plots
@@ -19,7 +19,7 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
@click.command(
- entry_point_group="mednet.libs.classification.config",
+ entry_point_group="mednet.config",
cls=ConfigCommand,
epilog="""Examples:
diff --git a/src/mednet/libs/classification/scripts/saliency/generate.py b/src/mednet/classify/scripts/saliency/generate.py
similarity index 89%
rename from src/mednet/libs/classification/scripts/saliency/generate.py
rename to src/mednet/classify/scripts/saliency/generate.py
index d80bbefb..8b220813 100644
--- a/src/mednet/libs/classification/scripts/saliency/generate.py
+++ b/src/mednet/classify/scripts/saliency/generate.py
@@ -8,15 +8,15 @@ import typing
import click
from clapper.click import ResourceOption, verbosity_option
from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
+from ....scripts.click import ConfigCommand
from ...models.typing import SaliencyMapAlgorithm
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
@click.command(
- entry_point_group="mednet.libs.classification.config",
+ entry_point_group="mednet.config",
cls=ConfigCommand,
epilog="""Examples:
@@ -169,37 +169,28 @@ def generate(
algorithm and trained model.
"""
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.scripts.predict import setup_datamodule
- from mednet.libs.common.scripts.utils import save_json_metadata
- from mednet.libs.common.utils.checkpointer import (
- get_checkpoint_to_run_inference,
- )
-
+ from ....engine.device import DeviceManager
+ from ....engine.trainer import validate_model_datamodule
+ from ....scripts.utils import save_json_metadata
+ from ....utils.checkpointer import get_checkpoint_to_run_inference
from ...engine.saliency.generator import run
+ from ...models.classification_model import ClassificationModel
- save_json_metadata(
- output_file=output_folder / "saliency-generation.meta.json",
- datamodule=datamodule,
- model=model,
- output_folder=output_folder,
- device=device,
- cache_samples=cache_samples,
- weight=weight,
- parallel=parallel,
- saliency_map_algorithm=saliency_map_algorithm,
- target_class=target_class,
- positive_only=positive_only,
- )
+ validate_model_datamodule(model, datamodule)
+ assert isinstance(model, ClassificationModel)
logger.info(f"Output folder: {output_folder}")
output_folder.mkdir(parents=True, exist_ok=True)
device_manager = DeviceManager(device)
+ # sets-up the data module
datamodule.cache_samples = cache_samples
- datamodule.model_transforms = model.model_transforms
- setup_datamodule(datamodule, model, 1, parallel)
+ datamodule.model_transforms = list(model.model_transforms)
+ datamodule.batch_size = 1
+ datamodule.parallel = -1
+ datamodule.prepare_data()
+ datamodule.setup(stage="predict")
if weight.is_dir():
weight = get_checkpoint_to_run_inference(weight)
@@ -207,6 +198,20 @@ def generate(
logger.info(f"Loading checkpoint from `{weight}`...")
model = type(model).load_from_checkpoint(weight, strict=False)
+ save_json_metadata(
+ output_file=output_folder / "saliency-generation.meta.json",
+ datamodule=datamodule,
+ model=model,
+ output_folder=output_folder,
+ device=device,
+ cache_samples=cache_samples,
+ weight=weight,
+ parallel=parallel,
+ saliency_map_algorithm=saliency_map_algorithm,
+ target_class=target_class,
+ positive_only=positive_only,
+ )
+
run(
model=model,
datamodule=datamodule,
diff --git a/src/mednet/libs/classification/scripts/saliency/interpretability.py b/src/mednet/classify/scripts/saliency/interpretability.py
similarity index 95%
rename from src/mednet/libs/classification/scripts/saliency/interpretability.py
rename to src/mednet/classify/scripts/saliency/interpretability.py
index d3b57f28..8d0f39e0 100644
--- a/src/mednet/libs/classification/scripts/saliency/interpretability.py
+++ b/src/mednet/classify/scripts/saliency/interpretability.py
@@ -7,13 +7,14 @@ import pathlib
import click
from clapper.click import ResourceOption, verbosity_option
from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
+
+from ....scripts.click import ConfigCommand
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
@click.command(
- entry_point_group="mednet.libs.classification.config",
+ entry_point_group="mednet.config",
cls=ConfigCommand,
epilog="""Examples:
@@ -120,11 +121,7 @@ def interpretability(
thresholding.
"""
- from mednet.libs.common.scripts.utils import (
- save_json_metadata,
- save_json_with_backup,
- )
-
+ from ....scripts.utils import save_json_metadata, save_json_with_backup
from ...engine.saliency.interpretability import run
datamodule.batch_size = 1
diff --git a/src/mednet/libs/classification/scripts/saliency/view.py b/src/mednet/classify/scripts/saliency/view.py
similarity index 96%
rename from src/mednet/libs/classification/scripts/saliency/view.py
rename to src/mednet/classify/scripts/saliency/view.py
index 226af150..02eb4015 100644
--- a/src/mednet/libs/classification/scripts/saliency/view.py
+++ b/src/mednet/classify/scripts/saliency/view.py
@@ -12,7 +12,7 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
@click.command(
- entry_point_group="mednet.libs.classification.config",
+ entry_point_group="mednet.config",
cls=ConfigCommand,
epilog="""Examples:
@@ -97,8 +97,7 @@ def view(
**_,
) -> None: # numpydoc ignore=PR01
"""Generate heatmaps for input CXRs based on existing saliency maps."""
- from mednet.libs.common.scripts.utils import save_json_metadata
-
+ from ....scripts.utils import save_json_metadata
from ...engine.saliency.viewer import run
logger.info(f"Output folder: {output_folder}")
diff --git a/src/mednet/libs/common/__init__.py b/src/mednet/config/__init__.py
similarity index 100%
rename from src/mednet/libs/common/__init__.py
rename to src/mednet/config/__init__.py
diff --git a/src/mednet/libs/common/config/__init__.py b/src/mednet/config/augmentations/__init__.py
similarity index 100%
rename from src/mednet/libs/common/config/__init__.py
rename to src/mednet/config/augmentations/__init__.py
diff --git a/src/mednet/libs/common/config/augmentations/affine.py b/src/mednet/config/augmentations/affine.py
similarity index 100%
rename from src/mednet/libs/common/config/augmentations/affine.py
rename to src/mednet/config/augmentations/affine.py
diff --git a/src/mednet/libs/common/config/augmentations/elastic.py b/src/mednet/config/augmentations/elastic.py
similarity index 52%
rename from src/mednet/libs/common/config/augmentations/elastic.py
rename to src/mednet/config/augmentations/elastic.py
index 0961632f..19e58141 100644
--- a/src/mednet/libs/common/config/augmentations/elastic.py
+++ b/src/mednet/config/augmentations/elastic.py
@@ -3,13 +3,13 @@
# SPDX-License-Identifier: GPL-3.0-or-later
"""Elastic deformation with 80% probability.
-This sole data augmentation was proposed by Pasa in the article
-"Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis
-Screening and Visualization".
+This sole data augmentation was proposed by Pasa in the article "Efficient Deep
+Network Architectures for Fast Chest X-Ray Tuberculosis Screening and
+Visualization".
Reference: [PASA-2019]_
"""
-from mednet.libs.common.data.augmentations import ElasticDeformation
+from ...data.augmentations import ElasticDeformation
augmentations = [ElasticDeformation(p=0.8)]
diff --git a/src/mednet/libs/common/config/augmentations/hflip.py b/src/mednet/config/augmentations/hflip.py
similarity index 100%
rename from src/mednet/libs/common/config/augmentations/hflip.py
rename to src/mednet/config/augmentations/hflip.py
diff --git a/src/mednet/libs/common/config/augmentations/hflip_affine.py b/src/mednet/config/augmentations/hflip_affine.py
similarity index 100%
rename from src/mednet/libs/common/config/augmentations/hflip_affine.py
rename to src/mednet/config/augmentations/hflip_affine.py
diff --git a/src/mednet/libs/common/config/augmentations/hflip_jitter_affine.py b/src/mednet/config/augmentations/hflip_jitter_affine.py
similarity index 100%
rename from src/mednet/libs/common/config/augmentations/hflip_jitter_affine.py
rename to src/mednet/config/augmentations/hflip_jitter_affine.py
diff --git a/src/mednet/libs/common/config/augmentations/jitter.py b/src/mednet/config/augmentations/jitter.py
similarity index 100%
rename from src/mednet/libs/common/config/augmentations/jitter.py
rename to src/mednet/config/augmentations/jitter.py
diff --git a/src/mednet/libs/common/data/__init__.py b/src/mednet/data/__init__.py
similarity index 100%
rename from src/mednet/libs/common/data/__init__.py
rename to src/mednet/data/__init__.py
diff --git a/src/mednet/libs/common/data/augmentations.py b/src/mednet/data/augmentations.py
similarity index 100%
rename from src/mednet/libs/common/data/augmentations.py
rename to src/mednet/data/augmentations.py
diff --git a/src/mednet/libs/common/data/datamodule.py b/src/mednet/data/datamodule.py
similarity index 99%
rename from src/mednet/libs/common/data/datamodule.py
rename to src/mednet/data/datamodule.py
index d5110557..cf282189 100644
--- a/src/mednet/libs/common/data/datamodule.py
+++ b/src/mednet/data/datamodule.py
@@ -353,6 +353,9 @@ class ConcatDataModule(lightning.LightningDataModule):
split_name
The name of the split used to group the samples into the various
datasets for training, validation and testing.
+ task
+ The task this datamodule generate samples for (e.g. ``classification``
+ or ``segmentation``).
cache_samples
If set, then issue raw data loading during ``prepare_data()``, and
serves samples from CPU memory. Otherwise, loads samples from disk on
@@ -391,6 +394,7 @@ class ConcatDataModule(lightning.LightningDataModule):
splits: ConcatDatabaseSplit,
database_name: str = "",
split_name: str = "",
+ task: str = "",
cache_samples: bool = False,
batch_size: int = 1,
drop_incomplete_batch: bool = False,
@@ -401,6 +405,7 @@ class ConcatDataModule(lightning.LightningDataModule):
self.splits = splits
self.database_name = database_name
self.split_name = split_name
+ self.task = task
for dataset_name, split_loaders in splits.items():
count = sum([len(k) for k, _ in split_loaders])
diff --git a/src/mednet/libs/common/data/image_utils.py b/src/mednet/data/image_utils.py
similarity index 100%
rename from src/mednet/libs/common/data/image_utils.py
rename to src/mednet/data/image_utils.py
diff --git a/src/mednet/libs/common/data/split.py b/src/mednet/data/split.py
similarity index 98%
rename from src/mednet/libs/common/data/split.py
rename to src/mednet/data/split.py
index aace283f..b438748a 100644
--- a/src/mednet/libs/common/data/split.py
+++ b/src/mednet/data/split.py
@@ -11,7 +11,8 @@ import pathlib
import typing
import torch
-from mednet.libs.common.data.typing import DatabaseSplit, RawDataLoader
+
+from ..data.typing import DatabaseSplit, RawDataLoader
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/common/data/typing.py b/src/mednet/data/typing.py
similarity index 100%
rename from src/mednet/libs/common/data/typing.py
rename to src/mednet/data/typing.py
diff --git a/src/mednet/libs/common/config/augmentations/__init__.py b/src/mednet/engine/__init__.py
similarity index 100%
rename from src/mednet/libs/common/config/augmentations/__init__.py
rename to src/mednet/engine/__init__.py
diff --git a/src/mednet/libs/common/engine/callbacks.py b/src/mednet/engine/callbacks.py
similarity index 100%
rename from src/mednet/libs/common/engine/callbacks.py
rename to src/mednet/engine/callbacks.py
diff --git a/src/mednet/libs/common/engine/device.py b/src/mednet/engine/device.py
similarity index 100%
rename from src/mednet/libs/common/engine/device.py
rename to src/mednet/engine/device.py
diff --git a/src/mednet/libs/common/engine/loggers.py b/src/mednet/engine/loggers.py
similarity index 100%
rename from src/mednet/libs/common/engine/loggers.py
rename to src/mednet/engine/loggers.py
diff --git a/src/mednet/libs/common/engine/trainer.py b/src/mednet/engine/trainer.py
similarity index 55%
rename from src/mednet/libs/common/engine/trainer.py
rename to src/mednet/engine/trainer.py
index 63d916bc..34b052b5 100644
--- a/src/mednet/libs/common/engine/trainer.py
+++ b/src/mednet/engine/trainer.py
@@ -9,6 +9,7 @@ import pathlib
import lightning.pytorch
import lightning.pytorch.callbacks
import lightning.pytorch.loggers
+import torch
from ..utils.checkpointer import CHECKPOINT_ALIASES
from ..utils.resources import ResourceMonitor
@@ -18,6 +19,128 @@ from .device import DeviceManager
logger = logging.getLogger(__name__)
+def get_checkpoint_file(results_dir: pathlib.Path) -> pathlib.Path | None:
+ """Return the path of the latest checkpoint if it exists.
+
+ Parameters
+ ----------
+ results_dir
+ Directory in which results are saved.
+
+ Returns
+ -------
+ Path to the latest checkpoint
+ """
+ from ..utils.checkpointer import get_checkpoint_to_resume_training
+
+ checkpoint_file = None
+ if results_dir.is_dir():
+ try:
+ checkpoint_file = get_checkpoint_to_resume_training(results_dir)
+ except FileNotFoundError:
+ logger.info(
+ f"Folder {results_dir} already exists, but I did not"
+ f" find any usable checkpoint file to resume training"
+ f" from. Starting from scratch...",
+ )
+
+ return checkpoint_file
+
+
+def load_checkpoint(checkpoint_file, datamodule, model):
+ """Load the checkpoint.
+
+ Parameters
+ ----------
+ checkpoint_file
+ Path to the checkpoint.
+ datamodule
+ Instance of a Datamodule, used to set the model's normalizer.
+ model
+ The model corresponding to the checkpoint.
+ """
+
+ if checkpoint_file is None or not hasattr(model, "on_load_checkpoint"):
+ # Sets the model normalizer with the unaugmented-train-subset if we are
+ # starting from scratch and/or the model does not contain its own
+ # checkpoint loading strategy (e.g. a pytorch stock checkpoint). This
+ # call may be a NOOP, if the model comes from outside this framework,
+ # and expects different weights for the normalisation layer.
+ if hasattr(model, "set_normalizer"):
+ model.set_normalizer(datamodule.unshuffled_train_dataloader())
+ else:
+ logger.warning(
+ f"Model {model.name} has no `set_normalizer` method. "
+ "Skipping normalization setup (unsupported external model).",
+ )
+ else:
+ # Normalizer will be loaded during model.on_load_checkpoint
+ checkpoint = torch.load(checkpoint_file)
+ start_epoch = checkpoint["epoch"]
+ logger.info(
+ f"Resuming from epoch {start_epoch} "
+ f"(checkpoint file: `{str(checkpoint_file)}`)...",
+ )
+
+
+def setup_datamodule(
+ datamodule,
+ model,
+ batch_size,
+ drop_incomplete_batch,
+ cache_samples,
+ parallel,
+) -> None: # numpydoc ignore=PR01
+ """Configure and set up the datamodule."""
+ datamodule.batch_size = batch_size
+ datamodule.drop_incomplete_batch = drop_incomplete_batch
+ datamodule.cache_samples = cache_samples
+ datamodule.parallel = parallel
+ datamodule.model_transforms = model.model_transforms
+
+ datamodule.prepare_data()
+ datamodule.setup(stage="fit")
+
+
+def validate_model_datamodule(model, datamodule):
+ """Validate the use of a model and datamodule together.
+
+ Parameters
+ ----------
+ model
+ The model to be validated.
+ datamodule
+ The datamodule to be validated.
+
+ Raises
+ ------
+ TypeError
+ In case the types of both objects is not compatible.
+ """
+
+ from ..classify.models.classification_model import ClassificationModel
+ from ..segment.models.segmentation_model import SegmentationModel
+
+ # asserts data module and model are compatible
+ match model:
+ case ClassificationModel():
+ if datamodule.task != "classification":
+ raise TypeError(
+ f"Classification model `{model.name}` is incompatible with "
+ f"`{datamodule.task}` task from datamodule "
+ f"`{datamodule.database_name}`."
+ )
+ case SegmentationModel():
+ if datamodule.task != "segmentation":
+ raise TypeError(
+ f"Segmentation model `{model.name}` is incompatible with "
+ f"`{datamodule.task}` task from datamodule "
+ f"`{datamodule.database_name}`."
+ )
+ case _:
+ raise TypeError(f"Do not know how to handle model of type `{type(model)}`")
+
+
def run(
model: lightning.pytorch.LightningModule,
datamodule: lightning.pytorch.LightningDataModule,
diff --git a/src/mednet/engine/uploader.py b/src/mednet/engine/uploader.py
new file mode 100644
index 00000000..83dea4d3
--- /dev/null
+++ b/src/mednet/engine/uploader.py
@@ -0,0 +1,345 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+import configparser
+import json
+import logging
+import os
+import pathlib
+import shutil
+import tempfile
+import typing
+
+import gitlab
+import mlflow
+
+from ..utils.checkpointer import get_checkpoint_to_run_inference
+
+logger = logging.getLogger(__name__)
+
+
+def _gitlab_instance_and_token() -> tuple[gitlab.Gitlab, str]:
+ """Return an instance of the Gitlab object for remote operations, and the
+ user token.
+
+ Returns
+ -------
+ Gitlab main object and user token
+ """
+
+ cfg = pathlib.Path("~/.python-gitlab.cfg").expanduser()
+ if cfg.exists():
+ gl = gitlab.Gitlab.from_config("idiap", [str(cfg)])
+ config = configparser.ConfigParser()
+ config.read(cfg)
+ token = config["idiap"]["private_token"]
+
+ else: # ask the user for a token or use one from the current runner
+ server = "https://gitlab.idiap.ch"
+ token = input(f"{server} (user or project) token: ")
+ gl = gitlab.Gitlab(server, private_token=token, api_version="4")
+
+ # tests authentication with given credential.
+ gl.auth()
+
+ return gl, token
+
+
+def _size_in_mb(path: pathlib.Path) -> float:
+ """Return the size in megabytes of a file.
+
+ Parameters
+ ----------
+ path
+ Input path to calculate file size from.
+
+ Returns
+ -------
+ A floating point number for the size of the object in MB.
+ """
+ return path.stat().st_size / (1024**2)
+
+
+def _assemble_artifacts(
+ experiment_folder: pathlib.Path, upload_limit_mb: int
+) -> tempfile.TemporaryDirectory:
+ """Assemble artifacts (files) to upload, sanitize filenames and check overall upload
+ size.
+
+ The files that are uploaded are the following:
+
+ * train.meta.json: meta information during training
+ * trainlog.pdf: evolution of tracked training variables
+ * evaluation.json: evaluation results
+ * evaluation.meta.json: meta information during evaluation
+ * evaluation.rst: evaluation results in table format
+ * evaluation.pdf: evaluation plots
+ * model checkpoint (variable name)
+
+ Parameters
+ ----------
+ experiment_folder
+ Directory in which to upload results from.
+ upload_limit_mb
+ Maximim upload size in MB (set to 0 for no limit).
+
+ Returns
+ -------
+ Temporary directory where the important files from the experiment
+ folder have been assembled and names sanitized.
+
+ Raises
+ ------
+ AssertionError
+ In case one of the necessary files that are typically uploaded is
+ missing.
+ RuntimeError
+ In case the total size of the temporary directory contents is larger,
+ in MB, than the ``upload_limit_mb``.
+ """
+
+ logger.info(f"Assembling files from {experiment_folder}...")
+
+ # get train files
+ train_folder = experiment_folder
+ train_log_file = train_folder / "trainlog.pdf"
+ train_meta_file = train_folder / "train.meta.json"
+ train_model_file = get_checkpoint_to_run_inference(train_folder)
+ train_files = [train_meta_file, train_model_file, train_log_file]
+
+ # get evaluation files
+ evaluation_file = experiment_folder / "evaluation.json"
+ evaluation_meta_file = experiment_folder / "evaluation.meta.json"
+ evaluation_meta_file = experiment_folder / "evaluation.rst"
+ evaluation_log_file = experiment_folder / "evaluation.pdf"
+ evaluation_files = [
+ evaluation_file,
+ evaluation_meta_file,
+ evaluation_log_file,
+ ]
+
+ # checks all files exist
+ for f in train_files + evaluation_files:
+ assert f.exists(), f"Missing file `{f}` - cannot upload artifact"
+
+ # checks for maximum upload limit
+ total_size_mb = sum([_size_in_mb(f) for f in train_files + evaluation_files])
+ if upload_limit_mb != 0 and total_size_mb > upload_limit_mb:
+ raise RuntimeError(
+ f"Total size of upload ({total_size_mb:.2f} MB) exceeds "
+ f"permitted maximum ({upload_limit_mb:.2f} MB)."
+ )
+
+ retval = tempfile.TemporaryDirectory()
+ tmpdir_path = pathlib.Path(retval.name)
+ for f in train_files + evaluation_files:
+ clean = tmpdir_path / f.parts[-1].replace("=", "-")
+ shutil.copy2(f, clean)
+ logger.debug(f"`{str(f)}` -> `{str(clean)}` ({_size_in_mb(f):.2f} MB)")
+
+ logger.info(f"Total size of files at {retval.name} = {total_size_mb:.2f} MB")
+ return retval
+
+
+def _assemble_parameters(basedir: pathlib.Path) -> dict[str, typing.Any]:
+ """Assemble parameters to log to experiment.
+
+ Parameters are forcebly converted to string representations via the MLflow
+ interface.
+
+ Parameters
+ ----------
+ basedir
+ Base directory where to find the file ``train.meta.json``. Typically,
+ this is the experiment folder.
+
+ Returns
+ -------
+ A dictionary that maps strings to any value that, itself, can be
+ converted to a string. The MLflow interface will take care of this.
+ """
+
+ train_meta_file = basedir / "train.meta.json"
+ with train_meta_file.open("r") as meta_file:
+ train_data = json.load(meta_file)
+
+ # get lowest validation epoch
+ train_model_file = get_checkpoint_to_run_inference(basedir)
+ best_epoch = int(str(train_model_file).split(".")[0].rsplit("=", 1)[1])
+
+ return {
+ "package version": train_data["package-version"],
+ "batch size": train_data["batch-size"],
+ "batch accumulations": train_data["accumulate-grad-batches"],
+ "epochs": train_data["epochs"],
+ "model epoch": best_epoch,
+ }
+
+
+def _assemble_metrics(basedir: pathlib.Path, names: list[str]) -> dict[str, float]:
+ """Assemble metrics to log to experiment.
+
+ Metrics are float values that can use to measure the performance of a
+ model.
+
+ Parameters
+ ----------
+ basedir
+ Base directory where to find the file ``evaluation.json``. Typically,
+ this is the experiment folder.
+ names
+ A list of metrics we are interested in fetching from the evaluation
+ file, and export to GitLab.
+
+ Returns
+ -------
+ A dictionary that maps strings to floating point values.
+ """
+
+ evaluation_file = basedir / "evaluation.json"
+ with evaluation_file.open("r") as f:
+ evaluation_data = json.load(f)
+
+ return {k: v for k, v in evaluation_data["test"].items() if k in names}
+
+
+def _user_or_default_names(
+ basedir: pathlib.Path, experiment_name: str, run_name: str
+) -> tuple[str, str]:
+ """Assert user-provided experiment and run names or defaults.
+
+ Parameters
+ ----------
+ basedir
+ Base directory where to find the file ``train.meta.json``. Typically,
+ this is the experiment folder.
+ experiment_name
+ User provided experiment name. If empty, then a default experiment
+ name will be proposed.
+ run_name
+ User provided run name. If empty, then a default run name using the
+ experiment date will be proposed.
+
+ Returns
+ -------
+ A tuple containing the experiment and run name to be used.
+ """
+
+ train_meta_file = basedir / "train.meta.json"
+ with train_meta_file.open("r") as meta_file:
+ train_data = json.load(meta_file)
+
+ return (
+ experiment_name or f"{train_data['model-name']}-{train_data['database-name']}",
+ run_name or train_data["datetime"],
+ )
+
+
+def _upload_ml_experiment(
+ project_path: str,
+ experiment_name: str,
+ run_name: str,
+ artifact_path: pathlib.Path,
+ parameters: dict[str, typing.Any],
+ metrics: dict[str, float],
+) -> None:
+ """Upload to GitLab using the Machine Learning Experiment Tracking
+ interface.
+
+ Information about the ML Experiment Tracking interface can be found at
+ https://docs.gitlab.com/ee/user/project/ml/experiment_tracking/
+
+ Parameters
+ ----------
+ project_path
+ Path to the project where to upload model entries.
+ experiment_name
+ A string indicating the experiment name (e.g. "exp-pasa-mc" or "exp-densenet-mc-ch").
+ run_name
+ A string indicating the run name (e.g. "run-1").
+ artifact_path
+ A base directory in which all contained files will be uploaded as
+ artifacts to the experiment entry.
+ parameters
+ All experiment parameters (``str`` -> ``str``) to log to the
+ experiment table.
+ metrics
+ All experiment metrics (``str`` -> ``float``) to log to the experiment
+ table.
+ """
+
+ logger.info("Retrieving GitLab credentials for access to hosted MLFlow server...")
+ gitlab, token = _gitlab_instance_and_token()
+ project = gitlab.projects.get(project_path)
+ os.environ["MLFLOW_TRACKING_TOKEN"] = token
+ os.environ["MLFLOW_TRACKING_URI"] = (
+ gitlab.api_url + f"/projects/{project.id}/ml/mlflow"
+ )
+
+ logger.info(
+ f"Uploading entry `{run_name}` to experiment `{experiment_name}` "
+ f"on GitLab project {project.name_with_namespace} (id: {project.id})..."
+ )
+ exp_meta = mlflow.set_experiment(experiment_name=experiment_name)
+
+ with mlflow.start_run(run_name=run_name):
+ logger.info("Uploading parameters...")
+ for key, value in parameters.items():
+ logger.info(f'[parameter] "{key}" = "{str(value)}"')
+ mlflow.log_param(key, value, synchronous=True)
+
+ logger.info("Uploading metrics...")
+ for key, value in metrics.items():
+ logger.info(f'[metric] "{key}" = {value:.3g}')
+ mlflow.log_metric(key, value, synchronous=True)
+
+ logger.info("Uploading artifacts (files)...")
+ for f in artifact_path.glob("*.*"):
+ logger.info(f'[artifact] "{str(f)}" ({_size_in_mb(f):.2f} MB)')
+ mlflow.log_artifact(str(f))
+
+ logger.info(
+ f"Visit {gitlab.url}/{project.path_with_namespace}/-/ml/experiments/{exp_meta.experiment_id}"
+ )
+
+
+def run(
+ project_path: str,
+ experiment_folder: pathlib.Path,
+ experiment_name: str,
+ run_name: str,
+ metrics: list[str],
+ upload_limit_mb: int,
+) -> None:
+ """Upload results from an experiment folder to GitLab's MLFlow server.
+
+ Parameters
+ ----------
+ project_path
+ Path to the project where to upload model entries.
+ experiment_folder
+ Directory in which to upload results from.
+ experiment_name
+ A string indicating the experiment name (e.g. "exp-pasa-mc" or "exp-densenet-mc-ch").
+ run_name
+ A string indicating the run name (e.g. "run-1").
+ metrics
+ List of metrics to upload.
+ upload_limit_mb
+ Maximim upload size in MB (set to 0 for no limit).
+ """
+
+ tmpdir = _assemble_artifacts(experiment_folder, upload_limit_mb)
+
+ experiment_name, run_name = _user_or_default_names(
+ experiment_folder, experiment_name, run_name
+ )
+
+ _upload_ml_experiment(
+ project_path=project_path,
+ experiment_name=experiment_name,
+ run_name=run_name,
+ artifact_path=pathlib.Path(tmpdir.name),
+ parameters=_assemble_parameters(experiment_folder),
+ metrics=_assemble_metrics(experiment_folder, metrics),
+ )
diff --git a/src/mednet/libs/classification/scripts/cli.py b/src/mednet/libs/classification/scripts/cli.py
deleted file mode 100644
index f922cd7d..00000000
--- a/src/mednet/libs/classification/scripts/cli.py
+++ /dev/null
@@ -1,76 +0,0 @@
-# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import importlib
-
-import click
-from clapper.click import AliasedGroup
-
-
-@click.group(
- cls=AliasedGroup,
- context_settings=dict(help_option_names=["-?", "-h", "--help"]),
-)
-def classification():
- """Image classification benchmark."""
- pass
-
-
-classification.add_command(importlib.import_module("..config", package=__name__).config)
-classification.add_command(
- importlib.import_module("..database", package=__name__).database,
-)
-classification.add_command(
- importlib.import_module("..predict", package=__name__).predict
-)
-classification.add_command(importlib.import_module("..train", package=__name__).train)
-classification.add_command(
- importlib.import_module(
- "mednet.libs.common.scripts.train_analysis",
- package=__name__,
- ).train_analysis,
-)
-classification.add_command(
- importlib.import_module("..evaluate", package=__name__).evaluate,
-)
-classification.add_command(
- importlib.import_module("..experiment", package=__name__).experiment,
-)
-classification.add_command(
- importlib.import_module("..upload", package=__name__).upload,
-)
-
-
-@click.group(
- cls=AliasedGroup,
- context_settings=dict(help_option_names=["-?", "-h", "--help"]),
-)
-def saliency():
- """Generate, evaluate and view saliency maps."""
- pass
-
-
-classification.add_command(saliency)
-
-saliency.add_command(
- importlib.import_module("..saliency.generate", package=__name__).generate,
-)
-saliency.add_command(
- importlib.import_module(
- "..saliency.completeness",
- package=__name__,
- ).completeness,
-)
-saliency.add_command(
- importlib.import_module(
- "..saliency.interpretability",
- package=__name__,
- ).interpretability,
-)
-saliency.add_command(
- importlib.import_module("..saliency.evaluate", package=__name__).evaluate,
-)
-saliency.add_command(
- importlib.import_module("..saliency.view", package=__name__).view,
-)
diff --git a/src/mednet/libs/classification/scripts/config.py b/src/mednet/libs/classification/scripts/config.py
deleted file mode 100644
index 7d32cc1c..00000000
--- a/src/mednet/libs/classification/scripts/config.py
+++ /dev/null
@@ -1,107 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import click
-from clapper.click import AliasedGroup, verbosity_option
-from clapper.logging import setup
-from mednet.libs.common.scripts.config import copy as copy_
-from mednet.libs.common.scripts.config import describe as describe_
-from mednet.libs.common.scripts.config import list_ as list__
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-
-@click.group(cls=AliasedGroup)
-def config():
- """Command for listing, describing and copying configuration resources."""
- pass
-
-
-@config.command(
- name="list",
- epilog="""Examples:
-
-\b
- 1. Lists all configuration resources (type: mednet.libs.classification.config) installed:
-
- .. code:: sh
-
- mednet classification config list
-
-
-\b
- 2. Lists all configuration resources and their descriptions (notice this may
- be slow as it needs to load all modules once):
-
- .. code:: sh
-
- mednet classification config list -v
-
-""",
-)
-@verbosity_option(logger=logger)
-def list_(verbose) -> None: # numpydoc ignore=PR01
- """List configuration files installed."""
- list__("mednet.libs.classification.config", verbose)
-
-
-@config.command(
- epilog="""Examples:
-
-\b
- 1. Describe the Montgomery dataset configuration:
-
- .. code:: sh
-
- mednet classification config describe montgomery
-
-
-\b
- 2. Describe the Montgomery dataset configuration and lists its
- contents:
-
- .. code:: sh
-
- mednet classification config describe montgomery -v
-
-""",
-)
-@click.argument(
- "name",
- required=True,
- nargs=-1,
-)
-@verbosity_option(logger=logger)
-def describe(name, verbose) -> None: # numpydoc ignore=PR01
- """Describe a specific configuration file."""
- describe_(name, "mednet.libs.classification.config", verbose)
-
-
-@config.command(
- epilog="""Examples:
-
-\b
- 1. Make a copy of one of the stock configuration files locally, so it can be
- adapted:
-
- .. code:: sh
-
- $ mednet classification config copy montgomery -vvv newdataset.py
-
-""",
-)
-@click.argument(
- "source",
- required=True,
- nargs=1,
-)
-@click.argument(
- "destination",
- required=True,
- nargs=1,
-)
-@verbosity_option(logger=logger, expose_value=False)
-def copy(source, destination) -> None: # numpydoc ignore=PR01
- """Copy a specific configuration resource so it can be modified locally."""
- copy_(source, destination, "mednet.libs.classification.config")
diff --git a/src/mednet/libs/classification/scripts/database.py b/src/mednet/libs/classification/scripts/database.py
deleted file mode 100644
index 4cd6a414..00000000
--- a/src/mednet/libs/classification/scripts/database.py
+++ /dev/null
@@ -1,131 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import click
-from clapper.click import AliasedGroup, verbosity_option
-from clapper.logging import setup
-from mednet.libs.common.scripts.database import check as check_
-from mednet.libs.common.scripts.database import list_ as list__
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-
-def _get_raw_databases() -> dict[str, dict[str, str]]:
- """Return a list of all supported (raw) databases.
-
- Returns
- -------
- dict[str, dict[str, str]]
- Dictionary where keys are database names, and values are dictionaries
- containing two string keys:
-
- * ``module``: the full Pythonic module name (e.g.
- ``mednet.libs.classification.data.montgomery``).
- * ``datadir``: points to the user-configured data directory for the
- current dataset, if set, or ``None`` otherwise.
- """
-
- import importlib
- import pkgutil
-
- from mednet.libs.common.utils.rc import load_rc
-
- from ..config import data
-
- user_configuration = load_rc()
-
- retval = {}
- for k in pkgutil.iter_modules(data.__path__):
- for j in pkgutil.iter_modules(
- [next(iter(data.__path__)) + f"/{k.name}"],
- ):
- if j.name == "datamodule":
- # this is a submodule that can read raw data files
- module = importlib.import_module(
- f".{j.name}",
- data.__package__ + f".{k.name}",
- )
- if hasattr(module, "CONFIGURATION_KEY_DATADIR"):
- retval[k.name] = dict(
- module=module.__name__.rsplit(".", 1)[0],
- datadir=user_configuration.get(
- module.CONFIGURATION_KEY_DATADIR,
- ),
- )
- else:
- retval[k.name] = dict(module=module.__name__)
-
- return retval
-
-
-@click.group(cls=AliasedGroup)
-def database() -> None:
- """Command for listing and verifying databases installed."""
- pass
-
-
-@database.command(
- name="list",
- epilog="""Examples:
-
-\b
- 1. To install a database, set up its data directory ("datadir"). For
- example, to setup access to Montgomery files you downloaded locally at
- the directory "/path/to/montgomery/files", edit the RC file (typically
- ``$HOME/.config/mednet.libs.classification.toml``), and add a line like the following:
-
- .. code:: toml
-
- [datadir]
- montgomery = "/path/to/montgomery/files"
-
- .. note::
-
- This setting **is** case-sensitive.
-
-\b
- 2. List all raw databases supported (and configured):
-
- .. code:: sh
-
- $ mednet classification database list
-
-""",
-)
-@verbosity_option(logger=logger, expose_value=False)
-def list_():
- """List all supported and configured databases."""
-
- list__(_get_raw_databases())
-
-
-@database.command(
- epilog="""Examples:
-
- 1. Check if all files from the split 'montgomery-f0' of the Montgomery
- database can be loaded:
-
- .. code:: sh
-
- mednet classification datamodule check -vv montgomery-f0
-
-""",
-)
-@click.argument(
- "fold",
- nargs=1,
-)
-@click.option(
- "--limit",
- "-l",
- help="Limit check to the first N samples in each split dataset, making the "
- "check sensibly faster. Set it to zero (default) to check everything.",
- required=True,
- type=click.IntRange(0),
- default=0,
-)
-@verbosity_option(logger=logger, expose_value=False)
-def check(fold, limit): # numpydoc ignore=PR01
- """Check file access on one or more DataModules."""
- check_("mednet.libs.classification.config", fold, limit)
diff --git a/src/mednet/libs/classification/scripts/experiment.py b/src/mednet/libs/classification/scripts/experiment.py
deleted file mode 100644
index 5ce51f31..00000000
--- a/src/mednet/libs/classification/scripts/experiment.py
+++ /dev/null
@@ -1,161 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import json
-from datetime import datetime
-
-import click
-from clapper.click import ConfigCommand, ResourceOption, verbosity_option
-from clapper.logging import setup
-
-from .train import reusable_options as training_options
-
-# avoids X11/graphical desktop requirement when creating plots
-__import__("matplotlib").use("agg")
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-
-@click.command(
- entry_point_group="mednet.libs.classification.config",
- cls=ConfigCommand,
- epilog="""Examples:
-
- 1. Train a pasa model with montgomery dataset, on the CPU, for only two
- epochs, then runs inference and evaluation on stock datasets, report
- performance as a table and figures:
-
- .. code:: sh
-
- $ mednet classification experiment -vv pasa montgomery --epochs=2
-""",
-)
-@training_options
-@verbosity_option(logger=logger, cls=ResourceOption)
-@click.pass_context
-def experiment(
- ctx,
- model,
- output_folder,
- epochs,
- batch_size,
- accumulate_grad_batches,
- drop_incomplete_batch,
- datamodule,
- validation_period,
- device,
- cache_samples,
- seed,
- parallel,
- monitoring_interval,
- augmentations,
- **_,
-): # numpydoc ignore=PR01
- r"""Run a complete experiment, from training, to prediction and evaluation.
-
- This script is just a wrapper around the individual scripts for training,
- running prediction, and evaluating. It organises the output in a preset way:
-
- .. code::
-
- └─ <output-folder>/ # the generated model will be here
- ├── predictions.json # the prediction outputs
- ├── evaluation.json # the evaluation outputs
- """
-
- experiment_start_timestamp = datetime.now()
-
- train_start_timestamp = datetime.now()
- logger.info(f"Started training at {train_start_timestamp}")
-
- from .train import train
-
- ctx.invoke(
- train,
- model=model,
- output_folder=output_folder,
- epochs=epochs,
- batch_size=batch_size,
- accumulate_grad_batches=accumulate_grad_batches,
- drop_incomplete_batch=drop_incomplete_batch,
- datamodule=datamodule,
- validation_period=validation_period,
- device=device,
- cache_samples=cache_samples,
- seed=seed,
- parallel=parallel,
- monitoring_interval=monitoring_interval,
- augmentations=augmentations,
- )
- train_stop_timestamp = datetime.now()
-
- logger.info(f"Ended training at {train_stop_timestamp}")
- logger.info(f"Training runtime: {train_stop_timestamp-train_start_timestamp}")
-
- logger.info("Started train analysis")
- from mednet.libs.common.scripts.train_analysis import train_analysis
-
- logdir = output_folder / "logs"
- ctx.invoke(
- train_analysis,
- logdir=logdir,
- output_folder=output_folder,
- )
-
- logger.info("Ended train analysis")
-
- predict_start_timestamp = datetime.now()
- logger.info(f"Started prediction at {predict_start_timestamp}")
-
- from .predict import predict
-
- ctx.invoke(
- predict,
- output_folder=output_folder,
- model=model,
- datamodule=datamodule,
- device=device,
- weight=output_folder,
- batch_size=batch_size,
- parallel=parallel,
- )
-
- predict_stop_timestamp = datetime.now()
- logger.info(f"Ended prediction at {predict_stop_timestamp}")
- logger.info(f"Prediction runtime: {predict_stop_timestamp-predict_start_timestamp}")
-
- evaluation_start_timestamp = datetime.now()
- logger.info(f"Started evaluation at {evaluation_start_timestamp}")
-
- from .evaluate import evaluate
-
- predictions_file = output_folder / "predictions.json"
-
- with (output_folder / "predictions.json").open() as pf:
- splits = json.load(pf).keys()
-
- if "validation" in splits:
- evaluation_threshold = "validation"
- elif "train" in splits:
- evaluation_threshold = "train"
- else:
- evaluation_threshold = None
-
- ctx.invoke(
- evaluate,
- predictions=predictions_file,
- output_folder=output_folder,
- threshold=evaluation_threshold,
- )
-
- evaluation_stop_timestamp = datetime.now()
- logger.info(f"Ended prediction at {evaluation_stop_timestamp}")
- logger.info(
- f"Prediction runtime: {evaluation_stop_timestamp-evaluation_start_timestamp}"
- )
-
- experiment_stop_timestamp = datetime.now()
- logger.info(
- f"Total experiment runtime: {experiment_stop_timestamp-experiment_start_timestamp}"
- )
diff --git a/src/mednet/libs/classification/scripts/predict.py b/src/mednet/libs/classification/scripts/predict.py
deleted file mode 100644
index 9d2e5103..00000000
--- a/src/mednet/libs/classification/scripts/predict.py
+++ /dev/null
@@ -1,80 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-
-import click
-from clapper.click import ResourceOption, verbosity_option
-from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
-from mednet.libs.common.scripts.predict import reusable_options
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-
-@click.command(
- entry_point_group="mednet.libs.classification.config",
- cls=ConfigCommand,
- epilog="""Examples:
-
-1. Run prediction on an existing DataModule configuration:
-
- .. code:: sh
-
- mednet classification predict -vv pasa montgomery --weight=path/to/model.ckpt --output=path/to/predictions.json
-
-2. Enable multi-processing data loading with 6 processes:
-
- .. code:: sh
-
- mednet classification predict -vv pasa montgomery --parallel=6 --weight=path/to/model.ckpt --output=path/to/predictions.json
-
-""",
-)
-@reusable_options
-@verbosity_option(logger=logger, cls=ResourceOption, expose_value=False)
-def predict(
- output_folder,
- model,
- datamodule,
- batch_size,
- device,
- weight,
- parallel,
- **_,
-) -> None: # numpydoc ignore=PR01
- """Run inference (generates scores) on all input images, using a pre-trained model."""
-
- from mednet.libs.classification.engine.predictor import run
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.scripts.predict import (
- load_checkpoint,
- setup_datamodule,
- )
- from mednet.libs.common.scripts.utils import (
- save_json_metadata,
- save_json_with_backup,
- )
-
- predictions_meta_file = output_folder / "predictions.meta.json"
- predictions_meta_file.parent.mkdir(parents=True, exist_ok=True)
-
- setup_datamodule(datamodule, model, batch_size, parallel)
- model = load_checkpoint(model, weight)
- device_manager = DeviceManager(device)
- save_json_metadata(
- output_file=output_folder / "predictions.meta.json",
- output_folder=output_folder,
- model=model,
- datamodule=datamodule,
- batch_size=batch_size,
- device=device,
- weight=device,
- parallel=parallel,
- )
-
- predictions = run(model, datamodule, device_manager)
-
- predictions_file = output_folder / "predictions.json"
- save_json_with_backup(predictions_file, predictions)
- logger.info(f"Predictions saved to `{str(predictions_file)}`")
diff --git a/src/mednet/libs/classification/scripts/train.py b/src/mednet/libs/classification/scripts/train.py
deleted file mode 100644
index 87d0c23c..00000000
--- a/src/mednet/libs/classification/scripts/train.py
+++ /dev/null
@@ -1,130 +0,0 @@
-import click
-from clapper.click import ResourceOption, verbosity_option
-from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
-from mednet.libs.common.scripts.train import reusable_options
-
-logger = setup("mednet", format="%(levelname)s: %(message)s")
-
-
-@click.command(
- entry_point_group="mednet.libs.classification.config",
- cls=ConfigCommand,
- epilog="""Examples:
-
-1. Train a pasa model with the montgomery dataset, on a GPU (``cuda:0``), using
- simple elastic deformation augmentations:
-
- .. code:: sh
-
- mednet classification train -vv pasa elastic montgomery --batch-size=4 --device="cuda:0"
-""",
-)
-@reusable_options
-@click.option(
- "--balance-classes/--no-balance-classes",
- "-B/-N",
- help="""If set, balances weights of the random sampler during
- training so that samples from all sample classes are picked
- equitably.""",
- required=True,
- show_default=True,
- default=True,
- cls=ResourceOption,
-)
-@verbosity_option(logger=logger, cls=ResourceOption, expose_value=False)
-def train(
- model,
- output_folder,
- epochs,
- batch_size,
- accumulate_grad_batches,
- drop_incomplete_batch,
- datamodule,
- validation_period,
- device,
- cache_samples,
- seed,
- parallel,
- monitoring_interval,
- balance_classes,
- augmentations,
- **_,
-) -> None: # numpydoc ignore=PR01
- """Train an CNN to perform image classification.
-
- Training is performed for a configurable number of epochs, and
- generates checkpoints. Checkpoints are model files with a .ckpt
- extension that are used in subsequent tasks or from which training
- can be resumed.
- """
- from lightning.pytorch import seed_everything
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.engine.trainer import run
- from mednet.libs.common.scripts.train import (
- get_checkpoint_file,
- load_checkpoint,
- setup_datamodule,
- )
- from mednet.libs.common.scripts.utils import save_json_metadata
-
- seed_everything(seed)
-
- # report model/transforms options - set data augmentations
- logger.info(f"Network model: {type(model).__module__}.{type(model).__name__}")
- model.augmentation_transforms = augmentations
-
- device_manager = DeviceManager(device)
-
- # reset datamodule with user configurable options
- setup_datamodule(
- datamodule,
- model,
- batch_size,
- drop_incomplete_batch,
- cache_samples,
- parallel,
- )
-
- # If asked, rebalances the loss criterion based on the relative proportion
- # of class examples available in the training set. Also affects the
- # validation loss if a validation set is available on the DataModule.
- if balance_classes:
- logger.info("Applying train/valid loss balancing...")
- model.balance_losses(datamodule)
-
- checkpoint_file = get_checkpoint_file(output_folder)
- load_checkpoint(checkpoint_file, datamodule, model)
-
- # stores all information we can think of, to reproduce this later
- save_json_metadata(
- output_file=output_folder / "train.meta.json",
- datamodule=datamodule,
- model=model,
- device_manager=device_manager,
- output_folder=output_folder,
- epochs=epochs,
- batch_size=batch_size,
- accumulate_grad_batches=accumulate_grad_batches,
- drop_incomplete_batch=drop_incomplete_batch,
- validation_period=validation_period,
- cache_samples=cache_samples,
- seed=seed,
- parallel=parallel,
- monitoring_interval=monitoring_interval,
- balance_classes=balance_classes,
- )
-
- logger.info(f"Training for at most {epochs} epochs.")
-
- run(
- model=model,
- datamodule=datamodule,
- validation_period=validation_period,
- device_manager=device_manager,
- max_epochs=epochs,
- output_folder=output_folder,
- monitoring_interval=monitoring_interval,
- accumulate_grad_batches=accumulate_grad_batches,
- checkpoint=checkpoint_file,
- )
diff --git a/src/mednet/libs/classification/scripts/upload.py b/src/mednet/libs/classification/scripts/upload.py
deleted file mode 100644
index 5b653ce1..00000000
--- a/src/mednet/libs/classification/scripts/upload.py
+++ /dev/null
@@ -1,79 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import pathlib
-
-import click
-from clapper.click import ResourceOption, verbosity_option
-from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
-from mednet.libs.common.scripts.upload import reusable_options
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-
-@click.command(
- entry_point_group="mednet.libs.classification.config",
- cls=ConfigCommand,
- epilog="""Examples:
-
-1. Upload an existing experiment result from a path it resides on (with a default experiment name as {model-name}_{database-name} and a default run name as {date-time}):
-
- .. code:: sh
-
- mednet classification upload --experiment-folder=/path/to/results
-
-2. Upload an existing experiment result with an experiment name:
-
- .. code:: sh
-
- mednet classification upload --experiment-folder=/path/to/results --experiment-name=exp-pasa_mc
-
-3. Upload an existing experiment result with a run name:
-
- .. code:: sh
-
- mednet classification upload --experiment-folder=/path/to/results --run-name=run-1
-
-4. Upload an existing experiment result with defining a size limit of 20MB for each file:
-
- .. code:: sh
-
- mednet classification upload --experiment-folder=/path/to/results --upload-limit-mb=20
-
-""",
-)
-@reusable_options
-@verbosity_option(logger=logger, cls=ResourceOption, expose_value=False)
-def upload(
- project_path: str,
- experiment_folder: pathlib.Path,
- experiment_name: str,
- run_name: str,
- upload_limit_mb: int,
- **_, # ignored
-) -> None: # numpydoc ignore=PR01
- """Upload results from a classification experiment folder to GitLab's MLFlow server."""
-
- from mednet.libs.common.scripts.upload import upload as upload_
-
- metrics = [
- "threshold",
- "precision",
- "recall",
- "f1_score",
- "average_precision_score",
- "specificity",
- "auc_score",
- "accuracy",
- ]
-
- upload_(
- project_path,
- experiment_folder,
- experiment_name,
- run_name,
- metrics,
- upload_limit_mb,
- )
diff --git a/src/mednet/libs/classification/utils/gitlab.py b/src/mednet/libs/classification/utils/gitlab.py
deleted file mode 100644
index 0baeba83..00000000
--- a/src/mednet/libs/classification/utils/gitlab.py
+++ /dev/null
@@ -1,90 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import configparser
-import logging
-import pathlib
-import shutil
-
-import gitlab
-
-logger = logging.getLogger(__name__)
-
-
-def gitlab_instance_and_token() -> tuple[gitlab.Gitlab, str]:
- """Return an instance of the Gitlab object for remote operations, and the
- user token.
-
- Returns
- -------
- Gitlab main object and user token
- """
-
- cfg = pathlib.Path("~/.python-gitlab.cfg").expanduser()
- if cfg.exists():
- gl = gitlab.Gitlab.from_config("idiap", [str(cfg)])
- config = configparser.ConfigParser()
- config.read(cfg)
- token = config["idiap"]["private_token"]
-
- else: # ask the user for a token or use one from the current runner
- server = "https://gitlab.idiap.ch"
- token = input(f"{server} (user or project) token: ")
- gl = gitlab.Gitlab(server, private_token=token, api_version="4")
-
- # tests authentication with given credential.
- gl.auth()
-
- return gl, token
-
-
-def sanitize_filename(tmpdir: pathlib.Path, path: pathlib.Path) -> pathlib.Path:
- """Sanitize the name of a file to be logged.
-
- This function sanitizes the basename of a file to be logged on the GitLab
- MLflow server. It removes unsupported characters (such as ``=``) by
- creating a copy of the file to be uploaded, with a modified name, on the
- provided temporary directory. It then returns the name of such a temporary
- file.
-
- If the input file path does not need sanitization, it is returned as is.
-
- Parameters
- ----------
- tmpdir
- The temporary directory where a copy of the input path, with a
- sanitized name will be created.
- path
- The file that needs its name sanitized.
-
- Returns
- -------
- Path to the temporary folder, and the sanitized copy of the input file
- in said temporary folder, or the input ``path``, in case its name does not
- need sanitization.
- """
-
- sanitized_filename = path.parts[-1].replace("=", "-")
- if path.parts[-1] == sanitized_filename:
- return path
-
- absolute_sanitized_filename = tmpdir / sanitized_filename
- logger.info(f"Sanitazing filename `{path}` -> `{absolute_sanitized_filename}`")
- shutil.copy2(path, absolute_sanitized_filename)
- return absolute_sanitized_filename
-
-
-def size_in_mb(path: pathlib.Path) -> float:
- """Return the size in megabytes of a file.
-
- Parameters
- ----------
- path
- Input path to calculate file size from.
-
- Returns
- -------
- A floating point number for the size of the object in MB.
- """
- return path.stat().st_size / (1024**2)
diff --git a/src/mednet/libs/common/scripts/database.py b/src/mednet/libs/common/scripts/database.py
deleted file mode 100644
index 7bb561dc..00000000
--- a/src/mednet/libs/common/scripts/database.py
+++ /dev/null
@@ -1,102 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import click
-from clapper.logging import setup
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-
-def list_(config: dict[str, dict[str, str]]) -> None:
- """List all supported and configured databases.
-
- Parameters
- ----------
- config
- Dictionary where keys are database names, and values are dictionaries
- containing two string keys:
-
- * ``module``: the full Pythonic module name (e.g.
- ``mednet.libs.classification.data.montgomery``).
- * ``datadir``: points to the user-configured data directory for the
- current dataset, if set, or ``None`` otherwise.
- """
-
- click.echo("Available databases:")
- for k, v in config.items():
- if "datadir" not in v:
- # this database does not have a "datadir"
- continue
-
- if v["datadir"] is not None:
- click.secho(f'- {k} ({v["module"]}): "{v["datadir"]}"', fg="green")
- else:
- click.echo(f'- {k} ({v["module"]}): NOT installed')
-
-
-def check(entry_point_group, fold, limit): # numpydoc ignore=PR01
- """Check file access on one or more DataModules."""
- import importlib.metadata
- import sys
-
- click.secho(f"Checking fold `{fold}`...", fg="yellow")
- try:
- module = importlib.metadata.entry_points(group=entry_point_group)[fold].module
- except KeyError:
- raise Exception(f"Could not find database fold `{fold}`")
-
- datamodule = importlib.import_module(module).datamodule
-
- datamodule.model_transforms = [] # should be done before setup()
- datamodule.batch_size = 1 # ensure one sample is loaded at a time
- datamodule.setup("predict") # sets up all datasets
-
- loaders = datamodule.predict_dataloader()
-
- errors = 0
- for k, loader in loaders.items():
- if limit == 0:
- click.secho(
- f"Checking all samples of dataset `{k}` at fold `{fold}`...",
- fg="yellow",
- )
- loader_limit = sys.maxsize
- else:
- click.secho(
- f"Checking first {limit} samples of dataset "
- f"`{k}` at fold `{fold}`...",
- fg="yellow",
- )
- loader_limit = limit
- # the for loop will trigger raw data loading (ie. user code), protect
- # it
- try:
- for i, batch in enumerate(loader):
- if loader_limit == 0:
- break
- if isinstance(batch[0], dict):
- logger.info(
- f"{batch[1]['name'][0]}: "
- f"{[s for s in batch[0]['image'][0].shape]}@{batch[0]['image'][0].dtype}",
- )
- else:
- logger.info(
- f"{batch[1]['name'][0]}: "
- f"{[s for s in batch[0][0].shape]}@{batch[0][0].dtype}",
- )
- loader_limit -= 1
- except Exception:
- logger.exception(f"Unable to load batch {i} in dataset {k}")
- errors += 1
-
- if not errors:
- click.secho(
- f"OK! No errors were reported for database fold `{fold}`.",
- fg="green",
- )
- else:
- click.secho(
- f"Found {errors} errors loading DataModule `{fold}`.",
- fg="red",
- )
diff --git a/src/mednet/libs/common/scripts/predict.py b/src/mednet/libs/common/scripts/predict.py
deleted file mode 100644
index ac0e2e09..00000000
--- a/src/mednet/libs/common/scripts/predict.py
+++ /dev/null
@@ -1,165 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import functools
-import pathlib
-import typing
-
-import click
-import mednet.libs.common.data.datamodule
-import mednet.libs.common.models.model
-from clapper.logging import setup
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-
-def reusable_options(f: typing.Callable):
- """Wrap reusable predict script options for other scripts.
-
- This decorator equips the target function ``f`` with all (reusable)
- ``predict`` script options.
-
- Parameters
- ----------
- f
- The target function to equip with options. This function must have
- parameters that accept such options.
-
- Returns
- -------
- The decorated version of function ``f``
- """
- from clapper.click import ResourceOption
-
- @click.option(
- "--output-folder",
- "-o",
- help="Directory in which to save predictions (created if does not exist)",
- required=True,
- type=click.Path(
- file_okay=False,
- dir_okay=True,
- writable=True,
- path_type=pathlib.Path,
- ),
- default="predictions",
- cls=ResourceOption,
- )
- @click.option(
- "--model",
- "-m",
- help="""A lightning module instance implementing the network architecture
- (not the weights, necessarily) to be used for prediction.""",
- required=True,
- cls=ResourceOption,
- )
- @click.option(
- "--datamodule",
- "-d",
- help="""A lightning DataModule that will be asked for prediction data
- loaders. Typically, this includes all configured splits in a DataModule,
- however this is not a requirement. A DataModule that returns a single
- dataloader for prediction (wrapped in a dictionary) is acceptable.""",
- required=True,
- cls=ResourceOption,
- )
- @click.option(
- "--batch-size",
- "-b",
- help="""Number of samples in every batch (this parameter affects memory
- requirements for the network).""",
- required=True,
- show_default=True,
- default=1,
- type=click.IntRange(min=1),
- cls=ResourceOption,
- )
- @click.option(
- "--device",
- "-d",
- help='A string indicating the device to use (e.g. "cpu" or "cuda:0")',
- show_default=True,
- required=True,
- default="cpu",
- cls=ResourceOption,
- )
- @click.option(
- "--weight",
- "-w",
- help="""Path or URL to pretrained model file (`.ckpt` extension),
- corresponding to the architecture set with `--model`. Optionally, you may
- also pass a directory containing the result of a training session, in which
- case either the best (lowest validation) or latest model will be loaded.""",
- required=True,
- cls=ResourceOption,
- type=click.Path(
- exists=True,
- file_okay=True,
- dir_okay=True,
- readable=True,
- path_type=pathlib.Path,
- ),
- )
- @click.option(
- "--parallel",
- "-P",
- help="""Use multiprocessing for data loading: if set to -1 (default),
- disables multiprocessing data loading. Set to 0 to enable as many data
- loading instances as processing cores available in the system. Set to
- >= 1 to enable that many multiprocessing instances for data loading.""",
- type=click.IntRange(min=-1),
- show_default=True,
- required=True,
- default=-1,
- cls=ResourceOption,
- )
- @functools.wraps(f)
- def wrapper_reusable_options(*args, **kwargs):
- return f(*args, **kwargs)
-
- return wrapper_reusable_options
-
-
-def setup_datamodule(
- datamodule: mednet.libs.common.data.datamodule.ConcatDataModule,
- model: mednet.libs.common.models.model.Model,
- batch_size: int,
- parallel: int,
-) -> None: # numpydoc ignore=PR01
- """Configure and set up the datamodule."""
-
- datamodule.batch_size = batch_size
- datamodule.parallel = parallel
- datamodule.model_transforms = list(model.model_transforms)
-
- datamodule.prepare_data()
- datamodule.setup(stage="predict")
-
-
-def load_checkpoint(
- model: mednet.libs.common.models.model.Model, weight: pathlib.Path
-) -> mednet.libs.common.models.model.Model:
- """Load a model checkpoint for prediction.
-
- Parameters
- ----------
- model
- Instance of a model.
- weight
- The base directory containing either the "best", "last" or "periodic"
- checkpoint to start the training session from.
-
- Returns
- -------
- An instance of the model loaded from the checkpoint.
- """
- from mednet.libs.common.utils.checkpointer import (
- get_checkpoint_to_run_inference,
- )
-
- if weight.is_dir():
- weight = get_checkpoint_to_run_inference(weight)
-
- logger.info(f"Loading checkpoint from `{weight}`...")
- return type(model).load_from_checkpoint(weight, strict=False)
diff --git a/src/mednet/libs/common/scripts/upload.py b/src/mednet/libs/common/scripts/upload.py
deleted file mode 100644
index 3d51efbb..00000000
--- a/src/mednet/libs/common/scripts/upload.py
+++ /dev/null
@@ -1,220 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import functools
-import pathlib
-
-import click
-from clapper.click import ResourceOption
-from clapper.logging import setup
-
-# logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-logger = setup("mednet", format="%(levelname)s: %(message)s")
-
-
-def reusable_options(f):
- """Wrap reusable upload script options.
-
- This decorator equips the target function ``f`` with all (reusable)
- ``upload`` script options.
-
- Parameters
- ----------
- f
- The target function to equip with options. This function must have
- parameters that accept such options.
-
- Returns
- -------
- The decorated version of function ``f``
- """
-
- @click.option(
- "--project-path",
- "-p",
- help="Path to the project where to upload model entries",
- required=True,
- type=str,
- default="biosignal/software/mednet",
- show_default=True,
- cls=ResourceOption,
- )
- @click.option(
- "--experiment-folder",
- "-f",
- help="Directory in which to upload results from",
- required=True,
- type=click.Path(
- file_okay=False,
- dir_okay=True,
- path_type=pathlib.Path,
- ),
- default="results",
- show_default=True,
- cls=ResourceOption,
- )
- @click.option(
- "--experiment-name",
- "-e",
- help='A string indicating the experiment name (e.g. "exp-pasa-mc" or "exp-densenet-mc-ch")',
- cls=ResourceOption,
- )
- @click.option(
- "--run-name",
- "-r",
- help='A string indicating the run name (e.g. "run-1")',
- cls=ResourceOption,
- )
- @click.option(
- "--upload-limit-mb",
- "-l",
- help="Maximim upload size in MB (set to 0 for no limit).",
- show_default=True,
- required=True,
- default=10,
- type=click.IntRange(min=0),
- cls=ResourceOption,
- )
- @functools.wraps(f)
- def wrapper_reusable_options(*args, **kwargs):
- return f(*args, **kwargs)
-
- return wrapper_reusable_options
-
-
-def upload(
- project_path: str,
- experiment_folder: pathlib.Path,
- experiment_name: str,
- run_name: str,
- metrics: list[str],
- upload_limit_mb: int,
-) -> None:
- """Upload results from an experiment folder to GitLab's MLFlow server.
-
- Parameters
- ----------
- project_path
- Path to the project where to upload model entries.
- experiment_folder
- Directory in which to upload results from.
- experiment_name
- A string indicating the experiment name (e.g. "exp-pasa-mc" or "exp-densenet-mc-ch").
- run_name
- A string indicating the run name (e.g. "run-1").
- metrics
- List of metrics to upload.
- upload_limit_mb
- Maximim upload size in MB (set to 0 for no limit).
- """
-
- import json
- import os
- import tempfile
-
- import mlflow
- from mednet.libs.common.utils.checkpointer import (
- get_checkpoint_to_run_inference,
- )
- from mednet.libs.common.utils.gitlab import (
- gitlab_instance_and_token,
- sanitize_filename,
- size_in_mb,
- )
-
- logger.info("Retrieving GitLab credentials for access to hosted MLFlow server...")
- gitlab, token = gitlab_instance_and_token()
- project = gitlab.projects.get(project_path)
- os.environ["MLFLOW_TRACKING_TOKEN"] = token
- os.environ["MLFLOW_TRACKING_URI"] = (
- gitlab.api_url + f"/projects/{project.id}/ml/mlflow"
- )
-
- # get train files
- train_folder = experiment_folder
- train_log_file = train_folder / "trainlog.pdf"
- train_meta_file = train_folder / "train.meta.json"
- train_model_file = get_checkpoint_to_run_inference(train_folder)
- train_files = [train_meta_file, train_model_file, train_log_file]
-
- # get evaluation files
- evaluation_file = experiment_folder / "evaluation.json"
- evaluation_meta_file = experiment_folder / "evaluation.meta.json"
- evaluation_meta_file = experiment_folder / "evaluation.rst"
- evaluation_log_file = experiment_folder / "evaluation.pdf"
- evaluation_files = [
- evaluation_file,
- evaluation_meta_file,
- evaluation_log_file,
- ]
-
- # checks for maximum upload limit
- total_size_mb = sum([size_in_mb(f) for f in train_files + evaluation_files])
- if upload_limit_mb != 0 and total_size_mb > upload_limit_mb:
- raise RuntimeError(
- f"Total size of upload ({total_size_mb:.2f} MB) exceeds "
- f"permitted maximum ({upload_limit_mb:.2f} MB)."
- )
-
- with train_meta_file.open("r") as meta_file:
- train_data = json.load(meta_file)
-
- with evaluation_file.open("r") as meta_file:
- evaluation_data = json.load(meta_file)
- evaluation_data = evaluation_data["test"]
-
- # get lowest validation epoch
- best_epoch = str(train_model_file).split(".")[0].split("=")[1]
-
- experiment_name = (
- experiment_name or f"{train_data['model-name']}-{train_data['database-name']}"
- )
- run_name = run_name or train_data["datetime"]
-
- click.secho(
- f"Uploading entry `{run_name}` to experiment `{experiment_name}` "
- f"on GitLab project {project_path} (id: {project.id})...",
- bold=True,
- fg="green",
- )
- exp_meta = mlflow.set_experiment(experiment_name=experiment_name)
- with mlflow.start_run(run_name=run_name):
- click.echo("Uploading package metadata...")
- click.echo(f" -> `version` ({train_data['package-version']})")
- mlflow.log_param("package version", train_data["package-version"])
-
- click.echo("Uploading metrics...")
-
- for k in [
- "epochs",
- "batch-size",
- ]:
- click.secho(f" -> `{k}` ({train_data[k]})")
- mlflow.log_param(k, train_data[k])
-
- click.secho(f" -> `#accumulations` ({train_data['accumulate-grad-batches']})")
- mlflow.log_param("#Accumulations", train_data["accumulate-grad-batches"])
- click.secho(f" -> `epoch (best)` ({best_epoch})")
- mlflow.log_param("Epoch (best)", best_epoch)
-
- for k in metrics:
- click.secho(f" -> `{k}` ({evaluation_data[k]:.3g})")
- mlflow.log_metric(k, evaluation_data[k])
-
- click.echo("Uploading artifacts (files)...")
-
- with tempfile.TemporaryDirectory() as tmpdir_name:
- tmpdir = pathlib.Path(tmpdir_name)
- for f in train_files + evaluation_files:
- assert f.exists(), f"File `{f}` does not exist - cannot upload!"
- clean_path = str(sanitize_filename(tmpdir, f))
- click.secho(f" -> `{clean_path}` ({size_in_mb(f):.2f} MB)")
- mlflow.log_artifact(clean_path)
-
- click.secho(f"Uploaded {total_size_mb:.2f} MB to server.", bold=True, fg="green")
- click.secho(
- f"Visit {gitlab.url}/{project.path_with_namespace}/-/ml/experiments/{exp_meta.experiment_id}",
- bold=True,
- fg="blue",
- )
diff --git a/src/mednet/libs/common/utils/gitlab.py b/src/mednet/libs/common/utils/gitlab.py
deleted file mode 100644
index 0baeba83..00000000
--- a/src/mednet/libs/common/utils/gitlab.py
+++ /dev/null
@@ -1,90 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import configparser
-import logging
-import pathlib
-import shutil
-
-import gitlab
-
-logger = logging.getLogger(__name__)
-
-
-def gitlab_instance_and_token() -> tuple[gitlab.Gitlab, str]:
- """Return an instance of the Gitlab object for remote operations, and the
- user token.
-
- Returns
- -------
- Gitlab main object and user token
- """
-
- cfg = pathlib.Path("~/.python-gitlab.cfg").expanduser()
- if cfg.exists():
- gl = gitlab.Gitlab.from_config("idiap", [str(cfg)])
- config = configparser.ConfigParser()
- config.read(cfg)
- token = config["idiap"]["private_token"]
-
- else: # ask the user for a token or use one from the current runner
- server = "https://gitlab.idiap.ch"
- token = input(f"{server} (user or project) token: ")
- gl = gitlab.Gitlab(server, private_token=token, api_version="4")
-
- # tests authentication with given credential.
- gl.auth()
-
- return gl, token
-
-
-def sanitize_filename(tmpdir: pathlib.Path, path: pathlib.Path) -> pathlib.Path:
- """Sanitize the name of a file to be logged.
-
- This function sanitizes the basename of a file to be logged on the GitLab
- MLflow server. It removes unsupported characters (such as ``=``) by
- creating a copy of the file to be uploaded, with a modified name, on the
- provided temporary directory. It then returns the name of such a temporary
- file.
-
- If the input file path does not need sanitization, it is returned as is.
-
- Parameters
- ----------
- tmpdir
- The temporary directory where a copy of the input path, with a
- sanitized name will be created.
- path
- The file that needs its name sanitized.
-
- Returns
- -------
- Path to the temporary folder, and the sanitized copy of the input file
- in said temporary folder, or the input ``path``, in case its name does not
- need sanitization.
- """
-
- sanitized_filename = path.parts[-1].replace("=", "-")
- if path.parts[-1] == sanitized_filename:
- return path
-
- absolute_sanitized_filename = tmpdir / sanitized_filename
- logger.info(f"Sanitazing filename `{path}` -> `{absolute_sanitized_filename}`")
- shutil.copy2(path, absolute_sanitized_filename)
- return absolute_sanitized_filename
-
-
-def size_in_mb(path: pathlib.Path) -> float:
- """Return the size in megabytes of a file.
-
- Parameters
- ----------
- path
- Input path to calculate file size from.
-
- Returns
- -------
- A floating point number for the size of the object in MB.
- """
- return path.stat().st_size / (1024**2)
diff --git a/src/mednet/libs/segmentation/scripts/cli.py b/src/mednet/libs/segmentation/scripts/cli.py
deleted file mode 100644
index b6fa62ad..00000000
--- a/src/mednet/libs/segmentation/scripts/cli.py
+++ /dev/null
@@ -1,49 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import importlib
-
-import click
-from clapper.click import AliasedGroup
-
-from . import (
- config,
- database,
- dump_annotations,
- evaluate,
- predict,
- train,
- view,
-)
-
-
-@click.group(
- cls=AliasedGroup,
- context_settings=dict(help_option_names=["-?", "-h", "--help"]),
-)
-def segmentation():
- """Binary Segmentation Benchmark."""
- pass
-
-
-# segmentation.add_command(analyze.analyze)
-segmentation.add_command(config.config)
-segmentation.add_command(database.database)
-segmentation.add_command(train.train)
-segmentation.add_command(predict.predict)
-segmentation.add_command(evaluate.evaluate)
-segmentation.add_command(
- importlib.import_module(
- "mednet.libs.common.scripts.train_analysis",
- package=__name__,
- ).train_analysis,
-)
-segmentation.add_command(view.view)
-segmentation.add_command(dump_annotations.dump_annotations)
-segmentation.add_command(
- importlib.import_module("..experiment", package=__name__).experiment,
-)
-segmentation.add_command(
- importlib.import_module("..upload", package=__name__).upload,
-)
diff --git a/src/mednet/libs/segmentation/scripts/click.py b/src/mednet/libs/segmentation/scripts/click.py
deleted file mode 100644
index b028e6a7..00000000
--- a/src/mednet/libs/segmentation/scripts/click.py
+++ /dev/null
@@ -1,28 +0,0 @@
-# Copyright © 2022 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import click
-from clapper.click import ConfigCommand as _BaseConfigCommand
-
-
-class ConfigCommand(_BaseConfigCommand):
- """A click command-class that has the properties of :py:class:`clapper.click.ConfigCommand` and adds verbatim epilog formatting."""
-
- def format_epilog(
- self, _: click.core.Context, formatter: click.formatting.HelpFormatter
- ) -> None:
- """Format the command epilog during --help.
-
- Parameters
- ----------
- _
- The current parsing context.
- formatter
- The formatter to use for printing text.
- """
-
- if self.epilog:
- formatter.write_paragraph()
- for line in self.epilog.split("\n"):
- formatter.write(line + "\n")
diff --git a/src/mednet/libs/segmentation/scripts/config.py b/src/mednet/libs/segmentation/scripts/config.py
deleted file mode 100644
index 8fef1df9..00000000
--- a/src/mednet/libs/segmentation/scripts/config.py
+++ /dev/null
@@ -1,107 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import click
-from clapper.click import AliasedGroup, verbosity_option
-from clapper.logging import setup
-from mednet.libs.common.scripts.config import copy as copy_
-from mednet.libs.common.scripts.config import describe as describe_
-from mednet.libs.common.scripts.config import list_ as list__
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-
-@click.group(cls=AliasedGroup)
-def config():
- """Command for listing, describing and copying configuration resources."""
- pass
-
-
-@config.command(
- name="list",
- epilog="""Examples:
-
-\b
- 1. Lists all configuration resources (type: mednet.libs.segmentation.config) installed:
-
- .. code:: sh
-
- mednet segmentation config list
-
-
-\b
- 2. Lists all configuration resources and their descriptions (notice this may
- be slow as it needs to load all modules once):
-
- .. code:: sh
-
- mednet segmentation config list -v
-
-""",
-)
-@verbosity_option(logger=logger)
-def list_(verbose) -> None: # numpydoc ignore=PR01
- """List configuration files installed."""
- list__("mednet.libs.segmentation.config", verbose)
-
-
-@config.command(
- epilog="""Examples:
-
-\b
- 1. Describe the Drive dataset configuration:
-
- .. code:: sh
-
- mednet segmentation config describe drive
-
-
-\b
- 2. Describe the Drive dataset configuration and lists its
- contents:
-
- .. code:: sh
-
- mednet segmentation config describe deive -v
-
-""",
-)
-@click.argument(
- "name",
- required=True,
- nargs=-1,
-)
-@verbosity_option(logger=logger)
-def describe(name, verbose) -> None: # numpydoc ignore=PR01
- """Describe a specific configuration file."""
- describe_(name, "mednet.libs.segmentation.config", verbose)
-
-
-@config.command(
- epilog="""Examples:
-
-\b
- 1. Make a copy of one of the stock configuration files locally, so it can be
- adapted:
-
- .. code:: sh
-
- $ mednet segmentation config copy drive -vvv newdataset.py
-
-""",
-)
-@click.argument(
- "source",
- required=True,
- nargs=1,
-)
-@click.argument(
- "destination",
- required=True,
- nargs=1,
-)
-@verbosity_option(logger=logger, expose_value=False)
-def copy(source, destination) -> None: # numpydoc ignore=PR01
- """Copy a specific configuration resource so it can be modified locally."""
- copy_(source, destination, "mednet.libs.segmentation.config")
diff --git a/src/mednet/libs/segmentation/scripts/database.py b/src/mednet/libs/segmentation/scripts/database.py
deleted file mode 100644
index 272d4a09..00000000
--- a/src/mednet/libs/segmentation/scripts/database.py
+++ /dev/null
@@ -1,130 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import click
-from clapper.click import AliasedGroup, verbosity_option
-from clapper.logging import setup
-from mednet.libs.common.scripts.database import check as check_
-from mednet.libs.common.scripts.database import list_ as list__
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-
-def _get_raw_databases() -> dict[str, dict[str, str]]:
- """Return a list of all supported (raw) databases.
-
- Returns
- -------
- dict[str, dict[str, str]]
- Dictionary where keys are database names, and values are dictionaries
- containing two string keys:
-
- * ``module``: the full Pythonic module name (e.g.
- ``mednet.libs.segmentation.data.drive``).
- * ``datadir``: points to the user-configured data directory for the
- current dataset, if set, or ``None`` otherwise.
- """
-
- import importlib
- import pkgutil
-
- from mednet.libs.common.utils.rc import load_rc
-
- from ..config import data
-
- user_configuration = load_rc()
-
- retval = {}
- for k in pkgutil.iter_modules(data.__path__):
- for j in pkgutil.iter_modules(
- [next(iter(data.__path__)) + f"/{k.name}"],
- ):
- if j.name == "datamodule":
- # this is a submodule that can read raw data files
- module = importlib.import_module(
- f".{j.name}",
- data.__package__ + f".{k.name}",
- )
- if hasattr(module, "CONFIGURATION_KEY_DATADIR"):
- retval[k.name] = dict(
- module=module.__name__.rsplit(".", 1)[0],
- datadir=user_configuration.get(
- module.CONFIGURATION_KEY_DATADIR,
- ),
- )
- else:
- retval[k.name] = dict(module=module.__name__)
-
- return retval
-
-
-@click.group(cls=AliasedGroup)
-def database() -> None:
- """Command for listing and verifying databases installed."""
- pass
-
-
-@database.command(
- name="list",
- epilog="""Examples:
-
-\b
- 1. To install a database, set up its data directory ("datadir"). For
- example, to setup access to Drive files you downloaded locally at
- the directory "/path/to/drive/files", edit the RC file (typically
- ``$HOME/.config/mednet.toml``), and add a line like the following:
-
- .. code:: toml
-
- [datadir]
- drive = "/path/to/drive/files"
-
- .. note::
-
- This setting **is** case-sensitive.
-
-\b
- 2. List all raw databases supported (and configured):
-
- .. code:: sh
-
- $ mednet segmentation database list
-
-""",
-)
-@verbosity_option(logger=logger, expose_value=False)
-def list_():
- """List all supported and configured databases."""
- list__(_get_raw_databases())
-
-
-@database.command(
- epilog="""Examples:
-
- 1. Check if all files from the fold 'default' of the Drive
- database can be loaded:
-
- .. code:: sh
-
- mednet segmentation database check -vv drive
-
-""",
-)
-@click.argument(
- "fold",
- nargs=1,
-)
-@click.option(
- "--limit",
- "-l",
- help="Limit check to the first N samples in each split dataset, making the "
- "check sensibly faster. Set it to zero (default) to check everything.",
- required=True,
- type=click.IntRange(0),
- default=0,
-)
-@verbosity_option(logger=logger, expose_value=False)
-def check(fold, limit): # numpydoc ignore=PR01
- """Check file access on one or more DataModules."""
- check_("mednet.libs.segmentation.config", fold, limit)
diff --git a/src/mednet/libs/segmentation/scripts/predict.py b/src/mednet/libs/segmentation/scripts/predict.py
deleted file mode 100644
index b82d70bb..00000000
--- a/src/mednet/libs/segmentation/scripts/predict.py
+++ /dev/null
@@ -1,81 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import clapper.click
-import clapper.logging
-import click
-import mednet.libs.common.scripts.click
-import mednet.libs.common.scripts.predict
-
-logger = clapper.logging.setup(
- __name__.split(".")[0], format="%(levelname)s: %(message)s"
-)
-
-
-@click.command(
- entry_point_group="mednet.libs.segmentation.config",
- cls=mednet.libs.common.scripts.click.ConfigCommand,
- epilog="""Examples:
-
-1. Run prediction on an existing DataModule configuration:
-
- .. code:: sh
-
- mednet segmentation predict -vv lwnet drive --weight=path/to/model.ckpt --output-folder=path/to/predictions
-
-2. Enable multi-processing data loading with 6 processes:
-
- .. code:: sh
-
- mednet segmentation predict -vv lwnet drive --parallel=6 --weight=path/to/model.ckpt --output-folder=path/to/predictions
-
-""",
-)
-@mednet.libs.common.scripts.predict.reusable_options
-@clapper.click.verbosity_option(
- logger=logger, cls=clapper.click.ResourceOption, expose_value=False
-)
-def predict(
- output_folder,
- model,
- datamodule,
- batch_size,
- device,
- weight,
- parallel,
- **_,
-) -> None: # numpydoc ignore=PR01
- """Run inference (generates scores) on all input images, using a pre-trained model."""
-
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.scripts.predict import (
- load_checkpoint,
- setup_datamodule,
- )
- from mednet.libs.common.scripts.utils import (
- save_json_metadata,
- save_json_with_backup,
- )
- from mednet.libs.segmentation.engine.predictor import run
-
- setup_datamodule(datamodule, model, batch_size, parallel)
- model = load_checkpoint(model, weight)
- device_manager = DeviceManager(device)
-
- save_json_metadata(
- output_file=output_folder / "predictions.meta.json",
- output_folder=output_folder,
- model=model,
- datamodule=datamodule,
- batch_size=batch_size,
- device=device,
- weight=weight,
- parallel=parallel,
- )
-
- predictions = run(model, datamodule, device_manager, output_folder)
-
- predictions_file = output_folder / "predictions.json"
- save_json_with_backup(predictions_file, predictions)
- logger.info(f"Predictions saved to `{str(predictions_file)}`")
diff --git a/src/mednet/libs/segmentation/scripts/train.py b/src/mednet/libs/segmentation/scripts/train.py
deleted file mode 100644
index 1bf5ec00..00000000
--- a/src/mednet/libs/segmentation/scripts/train.py
+++ /dev/null
@@ -1,109 +0,0 @@
-import click
-from clapper.click import ResourceOption, verbosity_option
-from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
-from mednet.libs.common.scripts.train import reusable_options
-
-logger = setup("mednet", format="%(levelname)s: %(message)s")
-
-
-@click.command(
- entry_point_group="mednet.libs.segmentation.config",
- cls=ConfigCommand,
- epilog="""Examples:
-
-1. Train a lwnet model with the frive dataset, on a GPU (``cuda:0``):
-
- .. code:: sh
-
- mednet segmentation train -vv lwnet drive --batch-size=4 --device="cuda:0"
-""",
-)
-@reusable_options
-@verbosity_option(logger=logger, cls=ResourceOption, expose_value=False)
-def train(
- model,
- output_folder,
- epochs,
- batch_size,
- accumulate_grad_batches,
- drop_incomplete_batch,
- datamodule,
- validation_period,
- device,
- cache_samples,
- seed,
- parallel,
- monitoring_interval,
- augmentations,
- **_,
-) -> None: # numpydoc ignore=PR01
- """Train an CNN to perform image segmentation.
-
- Training is performed for a configurable number of epochs, and
- generates checkpoints. Checkpoints are model files with a .ckpt
- extension that are used in subsequent tasks or from which training
- can be resumed.
- """
- from lightning.pytorch import seed_everything
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.engine.trainer import run
- from mednet.libs.common.scripts.train import (
- get_checkpoint_file,
- load_checkpoint,
- setup_datamodule,
- )
- from mednet.libs.common.scripts.utils import save_json_metadata
-
- seed_everything(seed)
-
- # report model/transforms options - set data augmentations
- logger.info(f"Network model: {type(model).__module__}.{type(model).__name__}")
- model.augmentation_transforms = augmentations
-
- device_manager = DeviceManager(device)
-
- # reset datamodule with user configurable options
- setup_datamodule(
- datamodule,
- model,
- batch_size,
- drop_incomplete_batch,
- cache_samples,
- parallel,
- )
-
- checkpoint_file = get_checkpoint_file(output_folder)
- load_checkpoint(checkpoint_file, datamodule, model)
-
- # stores all information we can think of, to reproduce this later
- save_json_metadata(
- output_file=output_folder / "train.meta.json",
- datamodule=datamodule,
- model=model,
- output_folder=output_folder,
- device_manager=device_manager,
- epochs=epochs,
- batch_size=batch_size,
- accumulate_grad_batches=accumulate_grad_batches,
- drop_incomplete_batch=drop_incomplete_batch,
- validation_period=validation_period,
- cache_samples=cache_samples,
- seed=seed,
- parallel=parallel,
- monitoring_interval=monitoring_interval,
- )
-
- logger.info(f"Training for at most {epochs} epochs.")
-
- run(
- model=model,
- datamodule=datamodule,
- validation_period=validation_period,
- device_manager=device_manager,
- max_epochs=epochs,
- output_folder=output_folder,
- monitoring_interval=monitoring_interval,
- accumulate_grad_batches=accumulate_grad_batches,
- checkpoint=checkpoint_file,
- )
diff --git a/src/mednet/libs/segmentation/scripts/upload.py b/src/mednet/libs/segmentation/scripts/upload.py
deleted file mode 100644
index 0de94332..00000000
--- a/src/mednet/libs/segmentation/scripts/upload.py
+++ /dev/null
@@ -1,78 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import pathlib
-
-import click
-from clapper.click import ResourceOption, verbosity_option
-from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
-from mednet.libs.common.scripts.upload import reusable_options
-
-logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-
-
-@click.command(
- entry_point_group="mednet.libs.segmentation.config",
- cls=ConfigCommand,
- epilog="""Examples:
-
-1. Upload an existing experiment result from a path it resides on (with a default experiment name as {model-name}_{database-name} and a default run name as {date-time}):
-
- .. code:: sh
-
- mednet segmentation upload --experiment-folder=/path/to/results
-
-2. Upload an existing experiment result with an experiment name:
-
- .. code:: sh
-
- mednet segmentation upload --experiment-folder=/path/to/results --experiment-name=exp-pasa_mc
-
-3. Upload an existing experiment result with a run name:
-
- .. code:: sh
-
- mednet segmentation upload --experiment-folder=/path/to/results --run-name=run-1
-
-4. Upload an existing experiment result with defining a size limit of 20MB for each file:
-
- .. code:: sh
-
- mednet segmentation upload --experiment-folder=/path/to/results --upload-limit-mb=20
-
-""",
-)
-@reusable_options
-@verbosity_option(logger=logger, cls=ResourceOption, expose_value=False)
-def upload(
- project_path: str,
- experiment_folder: pathlib.Path,
- experiment_name: str,
- run_name: str,
- upload_limit_mb: int,
- **_, # ignored
-) -> None: # numpydoc ignore=PR01
- """Upload results from a segmentation experiment folder to GitLab's MLFlow server."""
-
- from mednet.libs.common.scripts.upload import upload as upload_
-
- metrics = [
- "precision",
- "recall",
- "f1",
- "average_precision_score",
- "specificity",
- "auc_score",
- "accuracy",
- ]
-
- upload_(
- project_path,
- experiment_folder,
- experiment_name,
- run_name,
- metrics,
- upload_limit_mb,
- )
diff --git a/src/mednet/libs/common/engine/__init__.py b/src/mednet/models/__init__.py
similarity index 100%
rename from src/mednet/libs/common/engine/__init__.py
rename to src/mednet/models/__init__.py
diff --git a/src/mednet/libs/common/models/loss_weights.py b/src/mednet/models/loss_weights.py
similarity index 100%
rename from src/mednet/libs/common/models/loss_weights.py
rename to src/mednet/models/loss_weights.py
diff --git a/src/mednet/libs/common/models/model.py b/src/mednet/models/model.py
similarity index 99%
rename from src/mednet/libs/common/models/model.py
rename to src/mednet/models/model.py
index cc4bf033..cf47c4aa 100644
--- a/src/mednet/libs/common/models/model.py
+++ b/src/mednet/models/model.py
@@ -13,8 +13,8 @@ import torch.optim.lr_scheduler
import torch.optim.optimizer
import torch.utils.data
import torchvision.transforms
-from mednet.libs.common.data.typing import TransformSequence
+from ..data.typing import TransformSequence
from .loss_weights import get_positive_weights
from .typing import Checkpoint
diff --git a/src/mednet/libs/common/models/transforms.py b/src/mednet/models/transforms.py
similarity index 100%
rename from src/mednet/libs/common/models/transforms.py
rename to src/mednet/models/transforms.py
diff --git a/src/mednet/libs/common/models/typing.py b/src/mednet/models/typing.py
similarity index 100%
rename from src/mednet/libs/common/models/typing.py
rename to src/mednet/models/typing.py
diff --git a/src/mednet/scripts/cli.py b/src/mednet/scripts/cli.py
index 59df4ef6..5eba2d65 100644
--- a/src/mednet/scripts/cli.py
+++ b/src/mednet/scripts/cli.py
@@ -1,9 +1,11 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import importlib
+
import click
from clapper.click import AliasedGroup
-from mednet.libs.classification.scripts.cli import classification
-from mednet.libs.segmentation.scripts.cli import segmentation
-
-from .info import info
@click.group(
@@ -11,10 +13,23 @@ from .info import info
context_settings=dict(help_option_names=["-?", "-h", "--help"]),
)
def cli():
- """Image classification benchmark."""
+ """Medical image analysis AI toolbox."""
pass
-cli.add_command(classification)
-cli.add_command(segmentation)
-cli.add_command(info)
+def _add_command(module, obj):
+ cli.add_command(
+ getattr(importlib.import_module("." + module, package=__name__), obj)
+ )
+
+
+_add_command(".info", "info")
+_add_command(".config", "config")
+_add_command(".database", "database")
+_add_command(".train", "train")
+_add_command(".train_analysis", "train_analysis")
+_add_command(".predict", "predict")
+_add_command(".experiment", "experiment")
+_add_command(".upload", "upload")
+_add_command("..classify.scripts.cli", "classify")
+_add_command("..segment.scripts.cli", "segment")
diff --git a/src/mednet/libs/common/scripts/click.py b/src/mednet/scripts/click.py
similarity index 100%
rename from src/mednet/libs/common/scripts/click.py
rename to src/mednet/scripts/click.py
diff --git a/src/mednet/libs/common/scripts/config.py b/src/mednet/scripts/config.py
similarity index 61%
rename from src/mednet/libs/common/scripts/config.py
rename to src/mednet/scripts/config.py
index d4a8062b..c090117e 100644
--- a/src/mednet/libs/common/scripts/config.py
+++ b/src/mednet/scripts/config.py
@@ -2,23 +2,50 @@
#
# SPDX-License-Identifier: GPL-3.0-or-later
-import importlib.metadata
-import inspect
-import pathlib
-import typing
-
import click
+from clapper.click import AliasedGroup, verbosity_option
from clapper.logging import setup
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
-def list_(entry_point_group, verbose) -> None: # numpydoc ignore=PR01
+@click.group(cls=AliasedGroup)
+def config():
+ """Command for listing, describing and copying configuration resources."""
+ pass
+
+
+@config.command(
+ name="list",
+ epilog="""Examples:
+
+\b
+ 1. Lists all configuration resources installed:
+
+ .. code:: sh
+
+ mednet config list
+
+
+\b
+ 2. Lists all configuration resources and their descriptions (notice this may
+ be slow as it needs to load all modules once):
+
+ .. code:: sh
+
+ mednet config list -v
+
+""",
+)
+@verbosity_option(logger=logger)
+def list_(verbose) -> None: # numpydoc ignore=PR01
"""List configuration files installed."""
- entry_points = importlib.metadata.entry_points().select(
- group=entry_point_group,
- )
+ import importlib.metadata
+ import inspect
+ import typing
+
+ entry_points = importlib.metadata.entry_points().select(group="mednet.config")
entry_point_dict = {k.name: k for k in entry_points}
# all potential modules with configuration resources
@@ -66,11 +93,41 @@ def list_(entry_point_group, verbose) -> None: # numpydoc ignore=PR01
click.echo(print_string % (name, summary))
-def describe(name, entry_point_group, verbose) -> None: # numpydoc ignore=PR01
+@config.command(
+ epilog="""Examples:
+
+\b
+ 1. Describe the Montgomery dataset configuration:
+
+ .. code:: sh
+
+ mednet config describe montgomery
+
+
+\b
+ 2. Describe the Montgomery dataset configuration and lists its
+ contents:
+
+ .. code:: sh
+
+ mednet config describe montgomery -v
+
+""",
+)
+@click.argument(
+ "name",
+ required=True,
+ nargs=-1,
+)
+@verbosity_option(logger=logger)
+def describe(name, verbose) -> None: # numpydoc ignore=PR01
"""Describe a specific configuration file."""
- entry_points = importlib.metadata.entry_points().select(
- group=entry_point_group,
- )
+
+ import importlib.metadata
+ import inspect
+ import pathlib
+
+ entry_points = importlib.metadata.entry_points().select(group="mednet.config")
entry_point_dict = {k.name: k for k in entry_points}
for k in name:
@@ -93,13 +150,38 @@ def describe(name, entry_point_group, verbose) -> None: # numpydoc ignore=PR01
click.echo(inspect.getdoc(mod))
-def copy(source, destination, entry_point_group) -> None: # numpydoc ignore=PR01
+@config.command(
+ epilog="""Examples:
+
+\b
+ 1. Make a copy of one of the stock configuration files locally, so it can be
+ adapted:
+
+ .. code:: sh
+
+ $ mednet config copy montgomery -vvv newdataset.py
+
+""",
+)
+@click.argument(
+ "source",
+ required=True,
+ nargs=1,
+)
+@click.argument(
+ "destination",
+ required=True,
+ nargs=1,
+)
+@verbosity_option(logger=logger, expose_value=False)
+def copy(source, destination) -> None: # numpydoc ignore=PR01
"""Copy a specific configuration resource so it can be modified locally."""
+
+ import importlib.metadata
+ import inspect
import shutil
- entry_points = importlib.metadata.entry_points().select(
- group=entry_point_group,
- )
+ entry_points = importlib.metadata.entry_points().select(group="mednet.config")
entry_point_dict = {k.name: k for k in entry_points}
if source not in entry_point_dict:
diff --git a/src/mednet/scripts/database.py b/src/mednet/scripts/database.py
new file mode 100644
index 00000000..91735214
--- /dev/null
+++ b/src/mednet/scripts/database.py
@@ -0,0 +1,222 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import click
+from clapper.click import AliasedGroup, verbosity_option
+from clapper.logging import setup
+
+logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
+
+
+def _get_raw_databases() -> dict[str, dict[str, str | list]]:
+ """Return a list of all supported (raw) databases.
+
+ Returns
+ -------
+ dict[str, dict[str, str]]
+ Dictionary where keys are database names, and values are dictionaries
+ containing two string keys:
+
+ * ``module``: the full Pythonic module name (e.g.
+ ``mednet.classify.data.montgomery``).
+ * ``datadir``: points to the user-configured data directory for the
+ current dataset, if set, or ``None`` otherwise.
+ """
+
+ import importlib
+ import pkgutil
+ import typing
+
+ from ..classify.config import data as classify_data
+ from ..segment.config import data as segment_data
+ from ..utils.rc import load_rc
+
+ user_configuration = load_rc()
+
+ retval: dict[str, dict[str, typing.Any]] = {}
+ for data in (classify_data, segment_data):
+ for k in pkgutil.iter_modules(data.__path__):
+ for j in pkgutil.iter_modules(
+ [next(iter(data.__path__)) + f"/{k.name}"],
+ ):
+ if j.name == "datamodule":
+ # this is a submodule that can read raw data files
+ assert data.__package__ is not None
+ module = importlib.import_module(
+ f".{j.name}", data.__package__ + f".{k.name}"
+ )
+ if hasattr(module, "CONFIGURATION_KEY_DATADIR"):
+ retval.setdefault(
+ k.name,
+ dict(
+ module=[],
+ datadir=user_configuration.get(
+ module.CONFIGURATION_KEY_DATADIR
+ ),
+ ),
+ )["module"].append(module.__name__.rsplit(".", 1)[0])
+ else:
+ retval.setdefault(k.name, dict(module=[]))["module"].append(
+ module.__name__
+ )
+
+ return retval
+
+
+def _list_raw_databases():
+ """List raw datasets to a string representation."""
+
+ def _echo(left: str, right: str, color: str = "white") -> None:
+ s = [
+ click.style(left, bold=True),
+ click.style(": ", bold=True),
+ click.style(right, fg=color),
+ ]
+ click.echo("".join(s))
+
+ for k, v in _get_raw_databases().items():
+ if "datadir" not in v:
+ # this database does not have a "datadir"
+ continue
+
+ if v["datadir"] is not None:
+ _echo(f" - {k} ({', '.join(v['module'])})", f"{v['datadir']}", "green")
+ else:
+ _echo(f" - {k} ({', '.join(v['module'])})", "NOT installed", "red")
+
+
+@click.group(cls=AliasedGroup)
+def database() -> None:
+ """Command for listing and verifying databases installed."""
+ pass
+
+
+@database.command(
+ name="list",
+ epilog="""Examples:
+
+\b
+ 1. To install a database, set up its data directory ("datadir"). For
+ example, to setup access to Montgomery files you downloaded locally at
+ the directory "/path/to/montgomery/files", edit the RC file (typically
+ ``$HOME/.config/mednet.toml``), and add a line like the following:
+
+ .. code:: toml
+
+ [datadir]
+ montgomery = "/path/to/montgomery/files"
+
+ .. note::
+
+ This setting **is** case-sensitive.
+
+\b
+ 2. List all raw databases supported (and configured):
+
+ .. code:: sh
+
+ $ mednet database list
+
+""",
+)
+@verbosity_option(logger=logger, expose_value=False)
+def list_():
+ """List all supported and configured databases."""
+
+ _list_raw_databases()
+
+
+@database.command(
+ epilog="""Examples:
+
+ 1. Check if all files from the split 'montgomery-f0' of the Montgomery
+ database can be loaded:
+
+ .. code:: sh
+
+ mednet database check -vv montgomery-f0
+
+""",
+)
+@click.argument(
+ "entrypoint",
+ nargs=1,
+)
+@click.option(
+ "--limit",
+ "-l",
+ help="Limit check to the first N samples in each split dataset, making the "
+ "check sensibly faster. Set it to zero (default) to check everything.",
+ required=True,
+ type=click.IntRange(0),
+ default=0,
+)
+@verbosity_option(logger=logger, expose_value=False)
+def check(entrypoint, limit): # numpydoc ignore=PR01
+ """Check file access on one or more DataModules."""
+ import importlib.metadata
+ import sys
+
+ click.secho(f"Checking entrypoint `{entrypoint}`...", fg="yellow")
+ try:
+ module = importlib.metadata.entry_points(group="mednet.config")[
+ entrypoint
+ ].module
+ except KeyError:
+ raise Exception(f"Could not find database entrypoint `{entrypoint}`")
+
+ datamodule = importlib.import_module(module).datamodule
+
+ datamodule.model_transforms = [] # should be done before setup()
+ datamodule.batch_size = 1 # ensure one sample is loaded at a time
+ datamodule.setup("predict") # sets up all datasets
+
+ loaders = datamodule.predict_dataloader()
+
+ errors = 0
+ for k, loader in loaders.items():
+ if limit == 0:
+ click.secho(
+ f"Checking all samples of dataset `{k}` at entrypoint `{entrypoint}`...",
+ fg="yellow",
+ )
+ loader_limit = sys.maxsize
+ else:
+ click.secho(
+ f"Checking first {limit} samples of dataset "
+ f"`{k}` at entrypoint `{entrypoint}`...",
+ fg="yellow",
+ )
+ loader_limit = limit
+ # the for loop will trigger raw data loading (ie. user code), protect
+ # it
+ try:
+ for i, batch in enumerate(loader):
+ if loader_limit == 0:
+ break
+ if isinstance(batch[0], dict):
+ logger.info(
+ f"{batch[1]['name'][0]}: "
+ f"{[s for s in batch[0]['image'][0].shape]}@{batch[0]['image'][0].dtype}",
+ )
+ else:
+ logger.info(
+ f"{batch[1]['name'][0]}: "
+ f"{[s for s in batch[0][0].shape]}@{batch[0][0].dtype}",
+ )
+ loader_limit -= 1
+ except Exception:
+ logger.exception(f"Unable to load batch {i} in dataset {k}")
+ errors += 1
+
+ if not errors:
+ click.secho(
+ f"OK! No errors were reported for database entrypoint `{entrypoint}`.",
+ fg="green",
+ )
+ else:
+ click.secho(
+ f"Found {errors} errors loading DataModule `{entrypoint}`.",
+ fg="red",
+ )
diff --git a/src/mednet/libs/segmentation/scripts/experiment.py b/src/mednet/scripts/experiment.py
similarity index 77%
rename from src/mednet/libs/segmentation/scripts/experiment.py
rename to src/mednet/scripts/experiment.py
index 6a53edf7..acbc6dd9 100644
--- a/src/mednet/libs/segmentation/scripts/experiment.py
+++ b/src/mednet/scripts/experiment.py
@@ -18,18 +18,18 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
@click.command(
- entry_point_group="mednet.libs.segmentation.config",
+ entry_point_group="mednet.config",
cls=ConfigCommand,
epilog="""Examples:
\b
1. Train a lwnet model with drive dataset, on the CPU, for only two
- epochs, then runs inference and evaluation on stock datasets, report
- performance as a table and figures:
+ epochs, then runs prediction (inference) and evaluation on listed datasets,
+ report performance as a table and figures:
.. code:: sh
- $ mednet segmentation experiment -vv lwnet drive --epochs=2
+ $ mednet experiment -vv lwnet drive --epochs=2
""",
)
@training_options
@@ -51,17 +51,24 @@ def experiment(
parallel,
monitoring_interval,
augmentations,
+ balance_classes,
**_,
): # numpydoc ignore=PR01
- r"""Run a complete experiment, from training, to prediction and evaluation.
+ """Run a complete experiment, from training, to prediction and evaluation.
This script is just a wrapper around the individual scripts for training,
- running prediction, and evaluating. It organises the output in a preset way::
+ running prediction, and evaluating. It organises the output in a preset way:
+
+ .. code::
- \b
└─ <output-folder>/ # the generated model will be here
├── predictions.json # the prediction outputs
└── evaluation.json # the evaluation outputs
+
+ Note that complete experiments do not have options related to specific task
+ functionality. Only the most generic set of options is available. To
+ execute specific tasks, use the specialized command-line interfaces
+ available in task-specific command groups.
"""
experiment_start_timestamp = datetime.now()
@@ -87,6 +94,7 @@ def experiment(
parallel=parallel,
monitoring_interval=monitoring_interval,
augmentations=augmentations,
+ balance_classes=balance_classes,
)
train_stop_timestamp = datetime.now()
@@ -94,7 +102,7 @@ def experiment(
logger.info(f"Training runtime: {train_stop_timestamp-train_start_timestamp}")
logger.info("Started train analysis")
- from mednet.libs.common.scripts.train_analysis import train_analysis
+ from .train_analysis import train_analysis
logdir = output_folder / "logs"
ctx.invoke(
@@ -115,9 +123,9 @@ def experiment(
output_folder=output_folder,
model=model,
datamodule=datamodule,
+ batch_size=batch_size,
device=device,
weight=output_folder,
- batch_size=batch_size,
parallel=parallel,
)
@@ -128,8 +136,6 @@ def experiment(
evaluation_start_timestamp = datetime.now()
logger.info(f"Started evaluation at {evaluation_start_timestamp}")
- from .evaluate import evaluate
-
predictions_file = output_folder / "predictions.json"
with (predictions_file).open() as pf:
@@ -142,13 +148,23 @@ def experiment(
else:
evaluation_threshold = None
+ match datamodule.task:
+ case "classification":
+ from ..classify.scripts.evaluate import evaluate
+ case "segmentation":
+ from ..segment.scripts.evaluate import evaluate
+ case _:
+ raise click.BadParameter(
+ f"Do not know how to handle evaluation on `{datamodule.task}` "
+ f"task from `{type(datamodule).__module__}.{type(datamodule).__name__}`"
+ )
+
ctx.invoke(
evaluate,
predictions=predictions_file,
output_folder=output_folder,
threshold=evaluation_threshold,
- # metric="f1",
- # steps=100,
+ plot=True,
)
evaluation_stop_timestamp = datetime.now()
diff --git a/src/mednet/scripts/info.py b/src/mednet/scripts/info.py
index 620e1a9d..96617cc8 100644
--- a/src/mednet/scripts/info.py
+++ b/src/mednet/scripts/info.py
@@ -5,7 +5,6 @@
import click
from clapper.click import verbosity_option
from clapper.logging import setup
-from clapper.rc import UserDefaults
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
@@ -19,33 +18,6 @@ def _echo(left: str, right: str, color: str = "white") -> None:
click.echo("".join(s))
-def database_configuration(
- rc: UserDefaults, raw_databases: dict[str, dict[str, str]], lib_name: str
-):
- """Display the database configuration for a particular library.
-
- Parameters
- ----------
- rc
- The user defaults read from the user .toml configuration file.
- raw_databases
- List of all supported (raw) databases.
- lib_name
- Name of the library to show configurations for.
- """
-
- click.secho(f"configured {lib_name} databases:", bold=True)
- for k, v in raw_databases.items():
- if "datadir" not in v:
- # this database does not have a "datadir"
- continue
-
- if v["datadir"] is not None:
- _echo(f" - {k} ({v['module']})", f"{v['datadir']}", "green")
- else:
- _echo(f" - {k} ({v['module']})", "NOT installed", "red")
-
-
@click.command(
epilog="""Examples:
@@ -65,14 +37,9 @@ def info(
import typing
- from mednet.libs.classification.scripts.database import (
- _get_raw_databases as _get_raw_databases_classification,
- )
- from mednet.libs.common.scripts.utils import execution_metadata
- from mednet.libs.common.utils.rc import load_rc
- from mednet.libs.segmentation.scripts.database import (
- _get_raw_databases as _get_raw_databases_segmentation,
- )
+ from ..scripts.utils import execution_metadata
+ from ..utils.rc import load_rc
+ from .database import _list_raw_databases
m = execution_metadata()
@@ -89,18 +56,9 @@ def info(
if not rc.path.exists():
_echo("mednet configuration", f"{str(rc.path)} [MISSING]", "white")
else:
- _echo("mednet configuration file: ", str(rc.path), "white")
-
- database_configuration(
- rc,
- _get_raw_databases_classification(),
- "classification",
- )
- database_configuration(
- rc,
- _get_raw_databases_segmentation(),
- "segmentation",
- )
+ _echo("mednet configuration file", f"{str(rc.path)}", "white")
+ click.secho("databases:", bold=True)
+ _list_raw_databases()
click.secho("dependencies:", bold=True)
python = typing.cast(dict[str, str], m["python"])
diff --git a/src/mednet/scripts/predict.py b/src/mednet/scripts/predict.py
new file mode 100644
index 00000000..5f0dbff6
--- /dev/null
+++ b/src/mednet/scripts/predict.py
@@ -0,0 +1,188 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import pathlib
+
+import clapper.click
+import click
+from clapper.logging import setup
+
+from .click import ConfigCommand
+
+logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
+
+
+@click.command(
+ entry_point_group="mednet.config",
+ cls=ConfigCommand,
+ epilog="""Examples:
+
+1. Run prediction on an existing DataModule configuration:
+
+ .. code:: sh
+
+ mednet predict -vv lwnet drive --weight=path/to/model.ckpt --output-folder=path/to/predictions
+
+2. Enable multi-processing data loading with 6 processes:
+
+ .. code:: sh
+
+ mednet predict -vv lwnet drive --parallel=6 --weight=path/to/model.ckpt --output-folder=path/to/predictions
+
+""",
+)
+@click.option(
+ "--output-folder",
+ "-o",
+ help="Directory in which to save predictions (created if does not exist)",
+ required=True,
+ type=click.Path(
+ file_okay=False,
+ dir_okay=True,
+ writable=True,
+ path_type=pathlib.Path,
+ ),
+ default="predictions",
+ cls=clapper.click.ResourceOption,
+)
+@click.option(
+ "--model",
+ "-m",
+ help="""A lightning module instance implementing the network architecture
+ (not the weights, necessarily) to be used for prediction.""",
+ required=True,
+ cls=clapper.click.ResourceOption,
+)
+@click.option(
+ "--datamodule",
+ "-d",
+ help="""A lightning DataModule that will be asked for prediction data
+ loaders. Typically, this includes all configured splits in a DataModule,
+ however this is not a requirement. A DataModule that returns a single
+ dataloader for prediction (wrapped in a dictionary) is acceptable.""",
+ required=True,
+ cls=clapper.click.ResourceOption,
+)
+@click.option(
+ "--batch-size",
+ "-b",
+ help="""Number of samples in every batch (this parameter affects memory
+ requirements for the network).""",
+ required=True,
+ show_default=True,
+ default=1,
+ type=click.IntRange(min=1),
+ cls=clapper.click.ResourceOption,
+)
+@click.option(
+ "--device",
+ "-d",
+ help='A string indicating the device to use (e.g. "cpu" or "cuda:0")',
+ show_default=True,
+ required=True,
+ default="cpu",
+ cls=clapper.click.ResourceOption,
+)
+@click.option(
+ "--weight",
+ "-w",
+ help="""Path or URL to pretrained model file (`.ckpt` extension),
+ corresponding to the architecture set with `--model`. Optionally, you may
+ also pass a directory containing the result of a training session, in which
+ case either the best (lowest validation) or latest model will be loaded.""",
+ required=True,
+ cls=clapper.click.ResourceOption,
+ type=click.Path(
+ exists=True,
+ file_okay=True,
+ dir_okay=True,
+ readable=True,
+ path_type=pathlib.Path,
+ ),
+)
+@click.option(
+ "--parallel",
+ "-P",
+ help="""Use multiprocessing for data loading: if set to -1 (default),
+ disables multiprocessing data loading. Set to 0 to enable as many data
+ loading instances as processing cores available in the system. Set to
+ >= 1 to enable that many multiprocessing instances for data loading.""",
+ type=click.IntRange(min=-1),
+ show_default=True,
+ required=True,
+ default=-1,
+ cls=clapper.click.ResourceOption,
+)
+@clapper.click.verbosity_option(
+ logger=logger, cls=clapper.click.ResourceOption, expose_value=False
+)
+def predict(
+ output_folder,
+ model,
+ datamodule,
+ batch_size,
+ device,
+ weight,
+ parallel,
+ **_,
+) -> None: # numpydoc ignore=PR01
+ """Run inference on input samples, using a pre-trained model."""
+
+ from ..engine.device import DeviceManager
+ from ..engine.trainer import validate_model_datamodule
+ from ..scripts.utils import JSONable, save_json_metadata, save_json_with_backup
+ from ..utils.checkpointer import get_checkpoint_to_run_inference
+
+ validate_model_datamodule(model, datamodule)
+
+ # sets-up the data module
+ datamodule.batch_size = batch_size
+ datamodule.parallel = parallel
+ datamodule.model_transforms = list(model.model_transforms)
+
+ datamodule.prepare_data()
+ datamodule.setup(stage="predict")
+
+ if weight.is_dir():
+ weight = get_checkpoint_to_run_inference(weight)
+
+ logger.info(f"Loading checkpoint from `{weight}`...")
+ model = type(model).load_from_checkpoint(weight, strict=False)
+
+ device_manager = DeviceManager(device)
+
+ save_json_metadata(
+ output_file=output_folder / "predictions.meta.json",
+ output_folder=output_folder,
+ model=model,
+ datamodule=datamodule,
+ batch_size=batch_size,
+ device=device,
+ weight=weight,
+ parallel=parallel,
+ )
+
+ predictions: JSONable = None
+ match datamodule.task:
+ case "classification":
+ from ..classify.engine.predictor import run as run_classify
+
+ logger.info(f"Running prediction for `{datamodule.task}` task...")
+ predictions = run_classify(model, datamodule, device_manager)
+
+ case "segmentation":
+ from ..segment.engine.predictor import run as run_segment
+
+ logger.info(f"Running prediction for `{datamodule.task}` task...")
+ predictions = run_segment(model, datamodule, device_manager, output_folder)
+
+ case _:
+ raise click.BadParameter(
+ f"Do not know how to handle `{datamodule.task}` task from "
+ f"`{type(datamodule).__module__}.{type(datamodule).__name__}`"
+ )
+
+ predictions_file = output_folder / "predictions.json"
+ save_json_with_backup(predictions_file, predictions)
+ logger.info(f"Predictions saved to `{str(predictions_file)}`")
diff --git a/src/mednet/libs/common/scripts/train.py b/src/mednet/scripts/train.py
similarity index 66%
rename from src/mednet/libs/common/scripts/train.py
rename to src/mednet/scripts/train.py
index 52e78050..a6ff2db0 100644
--- a/src/mednet/libs/common/scripts/train.py
+++ b/src/mednet/scripts/train.py
@@ -6,10 +6,11 @@ import functools
import pathlib
import click
-from clapper.click import ResourceOption
+from clapper.click import ResourceOption, verbosity_option
from clapper.logging import setup
-# logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
+from ..scripts.click import ConfigCommand
+
logger = setup("mednet", format="%(levelname)s: %(message)s")
@@ -206,6 +207,17 @@ def reusable_options(f):
default=[],
cls=ResourceOption,
)
+ @click.option(
+ "--balance-classes/--no-balance-classes",
+ "-B/-N",
+ help="""If set, balances weights of the random sampler during
+ training so that samples from all sample classes are picked
+ equitably.""",
+ required=True,
+ show_default=True,
+ default=True,
+ cls=ResourceOption,
+ )
@functools.wraps(f)
def wrapper_reusable_options(*args, **kwargs):
return f(*args, **kwargs)
@@ -213,88 +225,122 @@ def reusable_options(f):
return wrapper_reusable_options
-def get_checkpoint_file(results_dir) -> pathlib.Path:
- """Return the path of the latest checkpoint if it exists.
+@click.command(
+ entry_point_group="mednet.config",
+ cls=ConfigCommand,
+ epilog="""Examples:
- Parameters
- ----------
- results_dir
- Directory in which results are saved.
+1. Train a Pasa model with the montgomery dataset (classification task):
- Returns
- -------
- Path to the latest checkpoint
- """
- from mednet.libs.common.utils.checkpointer import (
- get_checkpoint_to_resume_training,
- )
+ .. code:: sh
- checkpoint_file = None
- if results_dir.is_dir():
- try:
- checkpoint_file = get_checkpoint_to_resume_training(results_dir)
- except FileNotFoundError:
- logger.info(
- f"Folder {results_dir} already exists, but I did not"
- f" find any usable checkpoint file to resume training"
- f" from. Starting from scratch...",
- )
+ mednet train -vv pasa montgomery
- return checkpoint_file
+1. Train a Little WNet model with the drive dataset (vessel segmentation task):
+ .. code:: sh
-def load_checkpoint(checkpoint_file, datamodule, model):
- """Load the checkpoint.
+ mednet train -vv lwnet drive
+""",
+)
+@reusable_options
+@verbosity_option(logger=logger, cls=ResourceOption, expose_value=False)
+def train(
+ model,
+ output_folder,
+ epochs,
+ batch_size,
+ accumulate_grad_batches,
+ drop_incomplete_batch,
+ datamodule,
+ validation_period,
+ device,
+ cache_samples,
+ seed,
+ parallel,
+ monitoring_interval,
+ augmentations,
+ balance_classes,
+ **_,
+) -> None: # numpydoc ignore=PR01
+ """Train an CNN to perform image classification.
- Parameters
- ----------
- checkpoint_file
- Path to the checkpoint.
- datamodule
- Instance of a Datamodule, used to set the model's normalizer.
- model
- The model corresponding to the checkpoint.
+ Training is performed for a configurable number of epochs, and
+ generates checkpoints. Checkpoints are model files with a .ckpt
+ extension that are used in subsequent tasks or from which training
+ can be resumed.
"""
+ from lightning.pytorch import seed_everything
+
+ from ..engine.device import DeviceManager
+ from ..engine.trainer import (
+ get_checkpoint_file,
+ load_checkpoint,
+ run,
+ setup_datamodule,
+ validate_model_datamodule,
+ )
+ from ..scripts.utils import save_json_metadata
+
+ validate_model_datamodule(model, datamodule)
- import torch
+ seed_everything(seed)
- if checkpoint_file is None or not hasattr(model, "on_load_checkpoint"):
- # Sets the model normalizer with the unaugmented-train-subset if we are
- # starting from scratch and/or the model does not contain its own
- # checkpoint loading strategy (e.g. a pytorch stock checkpoint). This
- # call may be a NOOP, if the model comes from outside this framework,
- # and expects different weights for the normalisation layer.
- if hasattr(model, "set_normalizer"):
- model.set_normalizer(datamodule.unshuffled_train_dataloader())
+ # report model/transforms options - set data augmentations
+ logger.info(f"Network model: {type(model).__module__}.{type(model).__name__}")
+ model.augmentation_transforms = augmentations
+
+ device_manager = DeviceManager(device)
+
+ # reset datamodule with user configurable options
+ setup_datamodule(
+ datamodule, model, batch_size, drop_incomplete_batch, cache_samples, parallel
+ )
+
+ # If asked, rebalances the loss criterion based on the relative proportion
+ # of class examples available in the training set. Also affects the
+ # validation loss if a validation set is available on the DataModule.
+ if balance_classes:
+ if datamodule.task == "classification":
+ logger.info("Applying train/valid loss balancing...")
+ model.balance_losses(datamodule)
else:
- logger.warning(
- f"Model {model.name} has no `set_normalizer` method. "
- "Skipping normalization setup (unsupported external model).",
- )
- else:
- # Normalizer will be loaded during model.on_load_checkpoint
- checkpoint = torch.load(checkpoint_file)
- start_epoch = checkpoint["epoch"]
- logger.info(
- f"Resuming from epoch {start_epoch} "
- f"(checkpoint file: `{str(checkpoint_file)}`)...",
- )
+ logger.warn(f"Skipping loss balancing for {datamodule.task} task...")
+ balance_classes = False
+ checkpoint_file = get_checkpoint_file(output_folder)
+ load_checkpoint(checkpoint_file, datamodule, model)
-def setup_datamodule(
- datamodule,
- model,
- batch_size,
- drop_incomplete_batch,
- cache_samples,
- parallel,
-) -> None: # numpydoc ignore=PR01
- """Configure and set up the datamodule."""
- datamodule.batch_size = batch_size
- datamodule.drop_incomplete_batch = drop_incomplete_batch
- datamodule.cache_samples = cache_samples
- datamodule.parallel = parallel
- datamodule.model_transforms = model.model_transforms
+ # stores all information we can think of, to reproduce this later
+ save_json_metadata(
+ output_file=output_folder / "train.meta.json",
+ datamodule=datamodule,
+ model=model,
+ augmentations=augmentations,
+ device_manager=device_manager,
+ output_folder=output_folder,
+ epochs=epochs,
+ batch_size=batch_size,
+ accumulate_grad_batches=accumulate_grad_batches,
+ drop_incomplete_batch=drop_incomplete_batch,
+ validation_period=validation_period,
+ cache_samples=cache_samples,
+ seed=seed,
+ parallel=parallel,
+ monitoring_interval=monitoring_interval,
+ balance_classes=balance_classes,
+ )
- datamodule.prepare_data()
- datamodule.setup(stage="fit")
+ logger.info(f"Training for at most {epochs} epochs.")
+
+ run(
+ model=model,
+ datamodule=datamodule,
+ validation_period=validation_period,
+ device_manager=device_manager,
+ max_epochs=epochs,
+ output_folder=output_folder,
+ monitoring_interval=monitoring_interval,
+ accumulate_grad_batches=accumulate_grad_batches,
+ checkpoint=checkpoint_file,
+ )
diff --git a/src/mednet/libs/common/scripts/train_analysis.py b/src/mednet/scripts/train_analysis.py
similarity index 99%
rename from src/mednet/libs/common/scripts/train_analysis.py
rename to src/mednet/scripts/train_analysis.py
index 31c0de20..00ddebf9 100644
--- a/src/mednet/libs/common/scripts/train_analysis.py
+++ b/src/mednet/scripts/train_analysis.py
@@ -222,7 +222,8 @@ def train_analysis(
"""Create a plot for each metric in the training logs and saves them in a .pdf file."""
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
- from mednet.libs.common.utils.tensorboard import scalars_to_dict
+
+ from ..utils.tensorboard import scalars_to_dict
train_log_filename = "trainlog.pdf"
train_log_file = pathlib.Path(output_folder) / train_log_filename
diff --git a/src/mednet/scripts/upload.py b/src/mednet/scripts/upload.py
new file mode 100644
index 00000000..45b2296a
--- /dev/null
+++ b/src/mednet/scripts/upload.py
@@ -0,0 +1,128 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import pathlib
+
+import click
+from clapper.click import ResourceOption, verbosity_option
+from clapper.logging import setup
+
+from .click import ConfigCommand
+
+logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
+
+
+@click.command(
+ entry_point_group="mednet.config",
+ cls=ConfigCommand,
+ epilog="""Examples:
+
+1. Upload an existing experiment result from a path it resides on (with a default experiment name as {model-name}_{database-name} and a default run name as {date-time}):
+
+ .. code:: sh
+
+ mednet upload --experiment-folder=/path/to/results
+
+2. Upload an existing experiment result with an experiment name:
+
+ .. code:: sh
+
+ mednet upload --experiment-folder=/path/to/results --experiment-name=exp-pasa_mc
+
+3. Upload an existing experiment result with a run name:
+
+ .. code:: sh
+
+ mednet upload --experiment-folder=/path/to/results --run-name=run-1
+
+4. Upload an existing experiment result with defining a size limit of 20MB for each file:
+
+ .. code:: sh
+
+ mednet upload --experiment-folder=/path/to/results --upload-limit-mb=20
+
+""",
+)
+@click.option(
+ "--project-path",
+ "-p",
+ help="Path to the project where to upload model entries",
+ required=True,
+ type=str,
+ default="biosignal/software/mednet",
+ show_default=True,
+ cls=ResourceOption,
+)
+@click.option(
+ "--experiment-folder",
+ "-e",
+ help="Directory in which to upload results from",
+ required=True,
+ type=click.Path(
+ file_okay=False,
+ dir_okay=True,
+ path_type=pathlib.Path,
+ ),
+ default="results",
+ show_default=True,
+ cls=ResourceOption,
+)
+@click.option(
+ "--experiment-name",
+ "-n",
+ help='A string indicating the experiment name (e.g. "exp-pasa-mc" or "exp-densenet-mc-ch")',
+ required=True,
+ cls=ResourceOption,
+)
+@click.option(
+ "--run-name",
+ "-r",
+ help='A string indicating the run name (e.g. "run-1")',
+ required=True,
+ default="",
+ cls=ResourceOption,
+)
+@click.option(
+ "--upload-limit-mb",
+ "-l",
+ help="Maximim upload size in MB (set to 0 for no limit).",
+ show_default=True,
+ required=True,
+ default=10,
+ type=click.IntRange(min=0),
+ cls=ResourceOption,
+)
+@verbosity_option(logger=logger, cls=ResourceOption, expose_value=False)
+def upload(
+ project_path: str,
+ experiment_folder: pathlib.Path,
+ experiment_name: str,
+ run_name: str,
+ upload_limit_mb: int,
+ **_, # ignored
+) -> None: # numpydoc ignore=PR01
+ """Upload results from a classification experiment folder to GitLab's MLFlow server."""
+
+ from ..engine.uploader import run
+
+ # further metrics to be displayed
+ metrics = [
+ "threshold",
+ "precision",
+ "recall",
+ "f1",
+ "average_precision",
+ "specificity",
+ "roc_auc",
+ "accuracy",
+ ]
+
+ run(
+ project_path=project_path,
+ experiment_folder=experiment_folder,
+ experiment_name=experiment_name,
+ run_name=run_name,
+ metrics=metrics,
+ upload_limit_mb=upload_limit_mb,
+ )
diff --git a/src/mednet/libs/common/scripts/utils.py b/src/mednet/scripts/utils.py
similarity index 93%
rename from src/mednet/libs/common/scripts/utils.py
rename to src/mednet/scripts/utils.py
index cfc0a9c6..86eedabb 100644
--- a/src/mednet/libs/common/scripts/utils.py
+++ b/src/mednet/scripts/utils.py
@@ -14,7 +14,8 @@ import lightning.pytorch
import lightning.pytorch.callbacks
import numpy
import torch.nn
-from mednet.libs.common.engine.device import SupportedPytorchDevice
+
+from ..engine.device import SupportedPytorchDevice
logger = logging.getLogger(__name__)
@@ -71,11 +72,7 @@ def device_properties(
Static properties of the current machine.
"""
- from mednet.libs.common.utils.resources import (
- cpu_constants,
- cuda_constants,
- mps_constants,
- )
+ from ..utils.resources import cpu_constants, cuda_constants, mps_constants
retval: dict[str, int | float | str] = {}
retval.update(cpu_constants())
@@ -271,10 +268,9 @@ def save_json_metadata(
) -> None: # numpydoc ignore=PR01
"""Save prediction hyperparameters into a .json file."""
- from mednet.libs.common.data.datamodule import ConcatDataModule
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.models.model import Model
-
+ from ..data.datamodule import ConcatDataModule
+ from ..engine.device import DeviceManager
+ from ..models.model import Model
from .utils import (
device_properties,
execution_metadata,
@@ -290,12 +286,17 @@ def save_json_metadata(
json_data["database_name"] = value.database_name
json_data["database_split"] = value.split_name
case Model():
- json_data["model_name"] = value.name
+ json_data["model"] = f"{type(value).__module__}.{type(value).__name__}"
json_data.update(model_summary(value))
case pathlib.Path():
json_data[key] = str(value)
case DeviceManager():
json_data.update(device_properties(value.device_type))
+ case list() if key == "augmentations":
+ if len(value) != 0:
+ json_data[key] = [f"{type(k).__module__}.{str(k)}" for k in value]
+ else:
+ json_data[key] = []
case _:
json_data[key] = value
diff --git a/src/mednet/libs/common/models/__init__.py b/src/mednet/segment/__init__.py
similarity index 100%
rename from src/mednet/libs/common/models/__init__.py
rename to src/mednet/segment/__init__.py
diff --git a/src/mednet/libs/common/scripts/__init__.py b/src/mednet/segment/config/__init__.py
similarity index 100%
rename from src/mednet/libs/common/scripts/__init__.py
rename to src/mednet/segment/config/__init__.py
diff --git a/src/mednet/libs/common/utils/__init__.py b/src/mednet/segment/config/data/__init__.py
similarity index 100%
rename from src/mednet/libs/common/utils/__init__.py
rename to src/mednet/segment/config/data/__init__.py
diff --git a/src/mednet/libs/segmentation/__init__.py b/src/mednet/segment/config/data/avdrive/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/__init__.py
rename to src/mednet/segment/config/data/avdrive/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/avdrive/datamodule.py b/src/mednet/segment/config/data/avdrive/datamodule.py
similarity index 88%
rename from src/mednet/libs/segmentation/config/data/avdrive/datamodule.py
rename to src/mednet/segment/config/data/avdrive/datamodule.py
index 5567d27c..8d69b1d9 100644
--- a/src/mednet/libs/segmentation/config/data/avdrive/datamodule.py
+++ b/src/mednet/segment/config/data/avdrive/datamodule.py
@@ -7,17 +7,16 @@ import os
import pathlib
import PIL.Image
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -100,4 +99,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/avdrive/default.json b/src/mednet/segment/config/data/avdrive/default.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/avdrive/default.json
rename to src/mednet/segment/config/data/avdrive/default.json
diff --git a/src/mednet/libs/segmentation/config/data/avdrive/default.py b/src/mednet/segment/config/data/avdrive/default.py
similarity index 80%
rename from src/mednet/libs/segmentation/config/data/avdrive/default.py
rename to src/mednet/segment/config/data/avdrive/default.py
index e0e0603e..bf4970ec 100644
--- a/src/mednet/libs/segmentation/config/data/avdrive/default.py
+++ b/src/mednet/segment/config/data/avdrive/default.py
@@ -7,6 +7,6 @@
* We are using DRIVE dataset for artery vein segmentation
"""
-from mednet.libs.segmentation.config.data.avdrive.datamodule import DataModule
+from mednet.segment.config.data.avdrive.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/segmentation/config/data/avdrive/second-annotator.json b/src/mednet/segment/config/data/avdrive/second-annotator.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/avdrive/second-annotator.json
rename to src/mednet/segment/config/data/avdrive/second-annotator.json
diff --git a/src/mednet/libs/segmentation/config/__init__.py b/src/mednet/segment/config/data/chasedb1/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/__init__.py
rename to src/mednet/segment/config/data/chasedb1/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py b/src/mednet/segment/config/data/chasedb1/datamodule.py
similarity index 90%
rename from src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py
rename to src/mednet/segment/config/data/chasedb1/datamodule.py
index 16a12166..8ed0bb38 100644
--- a/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py
+++ b/src/mednet/segment/config/data/chasedb1/datamodule.py
@@ -8,17 +8,16 @@ import pathlib
import PIL.Image
import pkg_resources
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -113,4 +112,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/first-annotator.json b/src/mednet/segment/config/data/chasedb1/first-annotator.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/first-annotator.json
rename to src/mednet/segment/config/data/chasedb1/first-annotator.json
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/first_annotator.py b/src/mednet/segment/config/data/chasedb1/first_annotator.py
similarity index 74%
rename from src/mednet/libs/segmentation/config/data/chasedb1/first_annotator.py
rename to src/mednet/segment/config/data/chasedb1/first_annotator.py
index eae56453..120c9d3c 100644
--- a/src/mednet/libs/segmentation/config/data/chasedb1/first_annotator.py
+++ b/src/mednet/segment/config/data/chasedb1/first_annotator.py
@@ -3,6 +3,6 @@
# SPDX-License-Identifier: GPL-3.0-or-later
"""CHASE-DB1 dataset for Vessel Segmentation."""
-from mednet.libs.segmentation.config.data.chasedb1.datamodule import DataModule
+from mednet.segment.config.data.chasedb1.datamodule import DataModule
datamodule = DataModule("first-annotator.json")
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_01L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_01L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_01L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_01L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_01R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_01R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_01R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_01R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_02L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_02L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_02L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_02L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_02R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_02R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_02R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_02R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_03L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_03L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_03L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_03L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_03R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_03R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_03R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_03R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_04L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_04L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_04L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_04L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_04R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_04R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_04R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_04R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_05L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_05L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_05L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_05L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_05R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_05R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_05R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_05R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_06L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_06L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_06L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_06L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_06R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_06R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_06R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_06R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_07L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_07L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_07L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_07L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_07R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_07R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_07R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_07R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_08L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_08L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_08L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_08L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_08R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_08R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_08R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_08R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_09L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_09L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_09L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_09L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_09R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_09R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_09R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_09R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_10L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_10L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_10L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_10L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_10R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_10R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_10R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_10R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_11L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_11L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_11L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_11L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_11R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_11R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_11R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_11R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_12L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_12L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_12L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_12L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_12R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_12R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_12R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_12R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_13L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_13L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_13L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_13L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_13R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_13R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_13R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_13R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_14L.png b/src/mednet/segment/config/data/chasedb1/masks/Image_14L.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_14L.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_14L.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_14R.png b/src/mednet/segment/config/data/chasedb1/masks/Image_14R.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_14R.png
rename to src/mednet/segment/config/data/chasedb1/masks/Image_14R.png
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/second-annotator.json b/src/mednet/segment/config/data/chasedb1/second-annotator.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/second-annotator.json
rename to src/mednet/segment/config/data/chasedb1/second-annotator.json
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/second_annotator.py b/src/mednet/segment/config/data/chasedb1/second_annotator.py
similarity index 74%
rename from src/mednet/libs/segmentation/config/data/chasedb1/second_annotator.py
rename to src/mednet/segment/config/data/chasedb1/second_annotator.py
index 90c02cff..e276f768 100644
--- a/src/mednet/libs/segmentation/config/data/chasedb1/second_annotator.py
+++ b/src/mednet/segment/config/data/chasedb1/second_annotator.py
@@ -3,6 +3,6 @@
# SPDX-License-Identifier: GPL-3.0-or-later
"""CHASE-DB1 dataset for Vessel Segmentation."""
-from mednet.libs.segmentation.config.data.chasedb1.datamodule import DataModule
+from mednet.segment.config.data.chasedb1.datamodule import DataModule
datamodule = DataModule("second-annotator.json")
diff --git a/src/mednet/libs/segmentation/config/data/__init__.py b/src/mednet/segment/config/data/cxr8/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/__init__.py
rename to src/mednet/segment/config/data/cxr8/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/cxr8/datamodule.py b/src/mednet/segment/config/data/cxr8/datamodule.py
similarity index 92%
rename from src/mednet/libs/segmentation/config/data/cxr8/datamodule.py
rename to src/mednet/segment/config/data/cxr8/datamodule.py
index fee56bf0..c77a3bde 100644
--- a/src/mednet/libs/segmentation/config/data/cxr8/datamodule.py
+++ b/src/mednet/segment/config/data/cxr8/datamodule.py
@@ -9,16 +9,15 @@ import pathlib
import numpy as np
import PIL.Image
import torch
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -125,4 +124,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/cxr8/default.json.bz2 b/src/mednet/segment/config/data/cxr8/default.json.bz2
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/cxr8/default.json.bz2
rename to src/mednet/segment/config/data/cxr8/default.json.bz2
diff --git a/src/mednet/libs/segmentation/config/data/cxr8/default.py b/src/mednet/segment/config/data/cxr8/default.py
similarity index 76%
rename from src/mednet/libs/segmentation/config/data/cxr8/default.py
rename to src/mednet/segment/config/data/cxr8/default.py
index c736dd78..35d72a8d 100644
--- a/src/mednet/libs/segmentation/config/data/cxr8/default.py
+++ b/src/mednet/segment/config/data/cxr8/default.py
@@ -6,6 +6,6 @@
* Split reference: [GAAL-2020]_
"""
-from mednet.libs.segmentation.config.data.cxr8.datamodule import DataModule
+from mednet.segment.config.data.cxr8.datamodule import DataModule
datamodule = DataModule("default.json.bz2")
diff --git a/src/mednet/libs/segmentation/config/data/avdrive/__init__.py b/src/mednet/segment/config/data/drhagis/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/avdrive/__init__.py
rename to src/mednet/segment/config/data/drhagis/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/drhagis/datamodule.py b/src/mednet/segment/config/data/drhagis/datamodule.py
similarity index 88%
rename from src/mednet/libs/segmentation/config/data/drhagis/datamodule.py
rename to src/mednet/segment/config/data/drhagis/datamodule.py
index 1b0807dd..087773f1 100644
--- a/src/mednet/libs/segmentation/config/data/drhagis/datamodule.py
+++ b/src/mednet/segment/config/data/drhagis/datamodule.py
@@ -7,17 +7,16 @@ import os
import pathlib
import PIL.Image
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -101,4 +100,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/drhagis/default.json b/src/mednet/segment/config/data/drhagis/default.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drhagis/default.json
rename to src/mednet/segment/config/data/drhagis/default.json
diff --git a/src/mednet/libs/segmentation/config/data/drhagis/default.py b/src/mednet/segment/config/data/drhagis/default.py
similarity index 75%
rename from src/mednet/libs/segmentation/config/data/drhagis/default.py
rename to src/mednet/segment/config/data/drhagis/default.py
index 61122f80..55fd763f 100644
--- a/src/mednet/libs/segmentation/config/data/drhagis/default.py
+++ b/src/mednet/segment/config/data/drhagis/default.py
@@ -3,6 +3,6 @@
# SPDX-License-Identifier: GPL-3.0-or-later
"""DRHAGIS dataset for Vessel Segmentation (default protocol)."""
-from mednet.libs.segmentation.config.data.drhagis.datamodule import DataModule
+from mednet.segment.config.data.drhagis.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/__init__.py b/src/mednet/segment/config/data/drionsdb/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/chasedb1/__init__.py
rename to src/mednet/segment/config/data/drionsdb/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/datamodule.py b/src/mednet/segment/config/data/drionsdb/datamodule.py
similarity index 91%
rename from src/mednet/libs/segmentation/config/data/drionsdb/datamodule.py
rename to src/mednet/segment/config/data/drionsdb/datamodule.py
index 5e7076af..3ee5e033 100644
--- a/src/mednet/libs/segmentation/config/data/drionsdb/datamodule.py
+++ b/src/mednet/segment/config/data/drionsdb/datamodule.py
@@ -9,17 +9,16 @@ import pathlib
import PIL.Image
import pkg_resources
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -126,4 +125,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/expert1.json b/src/mednet/segment/config/data/drionsdb/expert1.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/expert1.json
rename to src/mednet/segment/config/data/drionsdb/expert1.json
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/expert1.py b/src/mednet/segment/config/data/drionsdb/expert1.py
similarity index 77%
rename from src/mednet/libs/segmentation/config/data/drionsdb/expert1.py
rename to src/mednet/segment/config/data/drionsdb/expert1.py
index c9339b09..605921c4 100644
--- a/src/mednet/libs/segmentation/config/data/drionsdb/expert1.py
+++ b/src/mednet/segment/config/data/drionsdb/expert1.py
@@ -6,6 +6,6 @@
* Split reference: [MANINIS-2016]_
"""
-from mednet.libs.segmentation.config.data.drionsdb.datamodule import DataModule
+from mednet.segment.config.data.drionsdb.datamodule import DataModule
datamodule = DataModule("expert1.json")
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/expert2.json b/src/mednet/segment/config/data/drionsdb/expert2.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/expert2.json
rename to src/mednet/segment/config/data/drionsdb/expert2.json
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/expert2.py b/src/mednet/segment/config/data/drionsdb/expert2.py
similarity index 77%
rename from src/mednet/libs/segmentation/config/data/drionsdb/expert2.py
rename to src/mednet/segment/config/data/drionsdb/expert2.py
index 9b6a344c..1009f3db 100644
--- a/src/mednet/libs/segmentation/config/data/drionsdb/expert2.py
+++ b/src/mednet/segment/config/data/drionsdb/expert2.py
@@ -6,6 +6,6 @@
* Split reference: [MANINIS-2016]_
"""
-from mednet.libs.segmentation.config.data.drionsdb.datamodule import DataModule
+from mednet.segment.config.data.drionsdb.datamodule import DataModule
datamodule = DataModule("expert2.json")
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_001.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_001.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_001.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_001.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_002.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_002.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_002.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_002.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_003.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_003.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_003.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_003.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_004.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_004.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_004.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_004.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_005.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_005.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_005.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_005.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_006.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_006.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_006.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_006.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_007.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_007.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_007.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_007.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_008.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_008.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_008.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_008.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_009.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_009.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_009.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_009.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_010.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_010.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_010.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_010.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_011.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_011.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_011.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_011.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_012.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_012.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_012.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_012.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_013.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_013.png
similarity index 100%
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similarity index 100%
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rename to src/mednet/segment/config/data/drionsdb/masks/images/image_075.png
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similarity index 100%
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rename to src/mednet/segment/config/data/drionsdb/masks/images/image_076.png
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similarity index 100%
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similarity index 100%
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similarity index 100%
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rename to src/mednet/segment/config/data/drionsdb/masks/images/image_079.png
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similarity index 100%
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similarity index 100%
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rename to src/mednet/segment/config/data/drionsdb/masks/images/image_081.png
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similarity index 100%
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rename to src/mednet/segment/config/data/drionsdb/masks/images/image_082.png
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similarity index 100%
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rename to src/mednet/segment/config/data/drionsdb/masks/images/image_083.png
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similarity index 100%
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rename to src/mednet/segment/config/data/drionsdb/masks/images/image_084.png
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similarity index 100%
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similarity index 100%
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similarity index 100%
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rename to src/mednet/segment/config/data/drionsdb/masks/images/image_087.png
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similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_088.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_088.png
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similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_089.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_089.png
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similarity index 100%
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rename to src/mednet/segment/config/data/drionsdb/masks/images/image_090.png
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similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_091.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_091.png
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similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_092.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_092.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_093.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_093.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_093.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_093.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_094.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_094.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_094.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_094.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_095.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_095.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_095.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_095.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_096.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_096.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_096.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_096.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_097.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_097.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_097.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_097.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_098.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_098.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_098.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_098.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_099.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_099.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_099.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_099.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_100.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_100.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_100.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_100.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_101.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_101.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_101.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_101.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_102.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_102.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_102.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_102.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_103.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_103.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_103.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_103.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_104.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_104.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_104.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_104.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_105.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_105.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_105.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_105.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_106.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_106.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_106.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_106.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_107.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_107.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_107.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_107.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_108.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_108.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_108.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_108.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_109.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_109.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_109.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_109.png
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_110.png b/src/mednet/segment/config/data/drionsdb/masks/images/image_110.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/masks/images/image_110.png
rename to src/mednet/segment/config/data/drionsdb/masks/images/image_110.png
diff --git a/src/mednet/libs/segmentation/config/data/cxr8/__init__.py b/src/mednet/segment/config/data/drishtigs1/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/cxr8/__init__.py
rename to src/mednet/segment/config/data/drishtigs1/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/datamodule.py b/src/mednet/segment/config/data/drishtigs1/datamodule.py
similarity index 91%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/datamodule.py
rename to src/mednet/segment/config/data/drishtigs1/datamodule.py
index 2ddc1b83..0f2ec919 100644
--- a/src/mednet/libs/segmentation/config/data/drishtigs1/datamodule.py
+++ b/src/mednet/segment/config/data/drishtigs1/datamodule.py
@@ -8,17 +8,16 @@ import pathlib
import PIL.Image
import pkg_resources
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -125,4 +124,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(target_all),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_001.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_001.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_001.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_001.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_003.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_003.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_003.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_003.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_005.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_005.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_005.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_005.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_006.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_006.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_006.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_006.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_007.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_007.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_007.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_007.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_009.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_009.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_009.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_009.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_011.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_011.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_011.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_011.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_013.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_013.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_013.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_013.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_014.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_014.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_014.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_014.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_019.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_019.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_019.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_019.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_020.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_020.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_020.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_020.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_021.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_021.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_021.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_021.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_023.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Test/Images/drishtiGS_023.png
similarity index 100%
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rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_088.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_088.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_089.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_089.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_089.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_089.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_090.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_090.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_090.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_090.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_092.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_092.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_092.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_092.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_094.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_094.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_094.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_094.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_098.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_098.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_098.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_098.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_101.png b/src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_101.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_101.png
rename to src/mednet/segment/config/data/drishtigs1/masks/Drishti-GS1_files/Training/Images/drishtiGS_101.png
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/optic-cup.json b/src/mednet/segment/config/data/drishtigs1/optic-cup.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/optic-cup.json
rename to src/mednet/segment/config/data/drishtigs1/optic-cup.json
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/optic-disc.json b/src/mednet/segment/config/data/drishtigs1/optic-disc.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/optic-disc.json
rename to src/mednet/segment/config/data/drishtigs1/optic-disc.json
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/optic_cup_all.py b/src/mednet/segment/config/data/drishtigs1/optic_cup_all.py
similarity index 79%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/optic_cup_all.py
rename to src/mednet/segment/config/data/drishtigs1/optic_cup_all.py
index 0bacacce..1d9fc8ad 100644
--- a/src/mednet/libs/segmentation/config/data/drishtigs1/optic_cup_all.py
+++ b/src/mednet/segment/config/data/drishtigs1/optic_cup_all.py
@@ -6,6 +6,6 @@
* Reference (includes split): [DRISHTIGS1-2014]_
"""
-from mednet.libs.segmentation.config.data.drishtigs1.datamodule import DataModule
+from mednet.segment.config.data.drishtigs1.datamodule import DataModule
datamodule = DataModule("optic-cup.json", target_all=True)
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/optic_cup_any.py b/src/mednet/segment/config/data/drishtigs1/optic_cup_any.py
similarity index 79%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/optic_cup_any.py
rename to src/mednet/segment/config/data/drishtigs1/optic_cup_any.py
index 668c051f..db24dc64 100644
--- a/src/mednet/libs/segmentation/config/data/drishtigs1/optic_cup_any.py
+++ b/src/mednet/segment/config/data/drishtigs1/optic_cup_any.py
@@ -6,6 +6,6 @@
* Reference (includes split): [DRISHTIGS1-2014]_
"""
-from mednet.libs.segmentation.config.data.drishtigs1.datamodule import DataModule
+from mednet.segment.config.data.drishtigs1.datamodule import DataModule
datamodule = DataModule("optic-cup.json", target_all=False)
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/optic_disc_all.py b/src/mednet/segment/config/data/drishtigs1/optic_disc_all.py
similarity index 79%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/optic_disc_all.py
rename to src/mednet/segment/config/data/drishtigs1/optic_disc_all.py
index 661224a6..6abaa31c 100644
--- a/src/mednet/libs/segmentation/config/data/drishtigs1/optic_disc_all.py
+++ b/src/mednet/segment/config/data/drishtigs1/optic_disc_all.py
@@ -6,6 +6,6 @@
* Reference (includes split): [DRISHTIGS1-2014]_
"""
-from mednet.libs.segmentation.config.data.drishtigs1.datamodule import DataModule
+from mednet.segment.config.data.drishtigs1.datamodule import DataModule
datamodule = DataModule("optic-disc.json", target_all=True)
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/optic_disc_any.py b/src/mednet/segment/config/data/drishtigs1/optic_disc_any.py
similarity index 79%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/optic_disc_any.py
rename to src/mednet/segment/config/data/drishtigs1/optic_disc_any.py
index 1192ffc3..bfa89b01 100644
--- a/src/mednet/libs/segmentation/config/data/drishtigs1/optic_disc_any.py
+++ b/src/mednet/segment/config/data/drishtigs1/optic_disc_any.py
@@ -6,6 +6,6 @@
* Reference (includes split): [DRISHTIGS1-2014]_
"""
-from mednet.libs.segmentation.config.data.drishtigs1.datamodule import DataModule
+from mednet.segment.config.data.drishtigs1.datamodule import DataModule
datamodule = DataModule("optic-disc.json", target_all=False)
diff --git a/src/mednet/libs/segmentation/config/data/drhagis/__init__.py b/src/mednet/segment/config/data/drive/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drhagis/__init__.py
rename to src/mednet/segment/config/data/drive/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/drive/datamodule.py b/src/mednet/segment/config/data/drive/datamodule.py
similarity index 88%
rename from src/mednet/libs/segmentation/config/data/drive/datamodule.py
rename to src/mednet/segment/config/data/drive/datamodule.py
index 01639da4..c15ad2d8 100644
--- a/src/mednet/libs/segmentation/config/data/drive/datamodule.py
+++ b/src/mednet/segment/config/data/drive/datamodule.py
@@ -7,17 +7,16 @@ import os
import pathlib
import PIL.Image
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -95,4 +94,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/drive/default.json b/src/mednet/segment/config/data/drive/default.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drive/default.json
rename to src/mednet/segment/config/data/drive/default.json
diff --git a/src/mednet/libs/segmentation/config/data/drive/default.py b/src/mednet/segment/config/data/drive/default.py
similarity index 78%
rename from src/mednet/libs/segmentation/config/data/drive/default.py
rename to src/mednet/segment/config/data/drive/default.py
index 383341b7..346ff97f 100644
--- a/src/mednet/libs/segmentation/config/data/drive/default.py
+++ b/src/mednet/segment/config/data/drive/default.py
@@ -6,6 +6,6 @@
* Split reference: [DRIVE-2004]_
"""
-from mednet.libs.segmentation.config.data.drive.datamodule import DataModule
+from mednet.segment.config.data.drive.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/segmentation/config/data/drive/drive_2nd.py b/src/mednet/segment/config/data/drive/drive_2nd.py
similarity index 82%
rename from src/mednet/libs/segmentation/config/data/drive/drive_2nd.py
rename to src/mednet/segment/config/data/drive/drive_2nd.py
index d700767c..7216b9f2 100644
--- a/src/mednet/libs/segmentation/config/data/drive/drive_2nd.py
+++ b/src/mednet/segment/config/data/drive/drive_2nd.py
@@ -7,6 +7,6 @@
* This dataset offers a second-annotator comparison for the test set only
"""
-from mednet.libs.segmentation.config.data.drive.datamodule import DataModule
+from mednet.segment.config.data.drive.datamodule import DataModule
datamodule = DataModule("second-annotator.json")
diff --git a/src/mednet/libs/segmentation/config/data/drive/second-annotator.json b/src/mednet/segment/config/data/drive/second-annotator.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drive/second-annotator.json
rename to src/mednet/segment/config/data/drive/second-annotator.json
diff --git a/src/mednet/libs/segmentation/config/data/drionsdb/__init__.py b/src/mednet/segment/config/data/hrf/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drionsdb/__init__.py
rename to src/mednet/segment/config/data/hrf/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/hrf/datamodule.py b/src/mednet/segment/config/data/hrf/datamodule.py
similarity index 88%
rename from src/mednet/libs/segmentation/config/data/hrf/datamodule.py
rename to src/mednet/segment/config/data/hrf/datamodule.py
index ed7ac302..9fc26cb4 100644
--- a/src/mednet/libs/segmentation/config/data/hrf/datamodule.py
+++ b/src/mednet/segment/config/data/hrf/datamodule.py
@@ -7,17 +7,16 @@ import os
import pathlib
import PIL.Image
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -97,4 +96,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/hrf/default.json b/src/mednet/segment/config/data/hrf/default.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/hrf/default.json
rename to src/mednet/segment/config/data/hrf/default.json
diff --git a/src/mednet/libs/segmentation/config/data/hrf/default.py b/src/mednet/segment/config/data/hrf/default.py
similarity index 76%
rename from src/mednet/libs/segmentation/config/data/hrf/default.py
rename to src/mednet/segment/config/data/hrf/default.py
index 855f6e26..4a0eea11 100644
--- a/src/mednet/libs/segmentation/config/data/hrf/default.py
+++ b/src/mednet/segment/config/data/hrf/default.py
@@ -6,8 +6,6 @@
* Split reference: [ORLANDO-2017]_
"""
-from mednet.libs.segmentation.config.data.hrf.datamodule import (
- DataModule,
-)
+from mednet.segment.config.data.hrf.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/segmentation/config/data/drishtigs1/__init__.py b/src/mednet/segment/config/data/iostar/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drishtigs1/__init__.py
rename to src/mednet/segment/config/data/iostar/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/iostar/datamodule.py b/src/mednet/segment/config/data/iostar/datamodule.py
similarity index 89%
rename from src/mednet/libs/segmentation/config/data/iostar/datamodule.py
rename to src/mednet/segment/config/data/iostar/datamodule.py
index 60283259..ea802914 100644
--- a/src/mednet/libs/segmentation/config/data/iostar/datamodule.py
+++ b/src/mednet/segment/config/data/iostar/datamodule.py
@@ -7,17 +7,16 @@ import os
import pathlib
import PIL.Image
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -101,4 +100,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/iostar/optic-disc.json b/src/mednet/segment/config/data/iostar/optic-disc.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/iostar/optic-disc.json
rename to src/mednet/segment/config/data/iostar/optic-disc.json
diff --git a/src/mednet/libs/segmentation/config/data/iostar/optic_disc.py b/src/mednet/segment/config/data/iostar/optic_disc.py
similarity index 78%
rename from src/mednet/libs/segmentation/config/data/iostar/optic_disc.py
rename to src/mednet/segment/config/data/iostar/optic_disc.py
index 10f9be60..bac2b29a 100644
--- a/src/mednet/libs/segmentation/config/data/iostar/optic_disc.py
+++ b/src/mednet/segment/config/data/iostar/optic_disc.py
@@ -7,6 +7,6 @@
* Split reference: [MEYER-2017]_
"""
-from mednet.libs.segmentation.config.data.iostar.datamodule import DataModule
+from mednet.segment.config.data.iostar.datamodule import DataModule
datamodule = DataModule("optic-disc.json")
diff --git a/src/mednet/libs/segmentation/config/data/iostar/vessel.json b/src/mednet/segment/config/data/iostar/vessel.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/iostar/vessel.json
rename to src/mednet/segment/config/data/iostar/vessel.json
diff --git a/src/mednet/libs/segmentation/config/data/iostar/vessel.py b/src/mednet/segment/config/data/iostar/vessel.py
similarity index 77%
rename from src/mednet/libs/segmentation/config/data/iostar/vessel.py
rename to src/mednet/segment/config/data/iostar/vessel.py
index 0b0c6486..9d237dc5 100644
--- a/src/mednet/libs/segmentation/config/data/iostar/vessel.py
+++ b/src/mednet/segment/config/data/iostar/vessel.py
@@ -7,6 +7,6 @@
* Split reference: [MEYER-2017]_
"""
-from mednet.libs.segmentation.config.data.iostar.datamodule import DataModule
+from mednet.segment.config.data.iostar.datamodule import DataModule
datamodule = DataModule("vessel.json")
diff --git a/src/mednet/libs/segmentation/config/data/drive/__init__.py b/src/mednet/segment/config/data/jsrt/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/drive/__init__.py
rename to src/mednet/segment/config/data/jsrt/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/jsrt/datamodule.py b/src/mednet/segment/config/data/jsrt/datamodule.py
similarity index 93%
rename from src/mednet/libs/segmentation/config/data/jsrt/datamodule.py
rename to src/mednet/segment/config/data/jsrt/datamodule.py
index ada65db9..41f556d6 100644
--- a/src/mednet/libs/segmentation/config/data/jsrt/datamodule.py
+++ b/src/mednet/segment/config/data/jsrt/datamodule.py
@@ -10,16 +10,15 @@ import numpy as np
import PIL.Image
import skimage.exposure
import torch
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -134,4 +133,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/jsrt/default.json b/src/mednet/segment/config/data/jsrt/default.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/jsrt/default.json
rename to src/mednet/segment/config/data/jsrt/default.json
diff --git a/src/mednet/libs/segmentation/config/data/jsrt/default.py b/src/mednet/segment/config/data/jsrt/default.py
similarity index 78%
rename from src/mednet/libs/segmentation/config/data/jsrt/default.py
rename to src/mednet/segment/config/data/jsrt/default.py
index 5b755e28..bf4c6e66 100644
--- a/src/mednet/libs/segmentation/config/data/jsrt/default.py
+++ b/src/mednet/segment/config/data/jsrt/default.py
@@ -7,8 +7,6 @@
* Split reference: [GAAL-2020]_
"""
-from mednet.libs.segmentation.config.data.jsrt.datamodule import (
- DataModule,
-)
+from mednet.segment.config.data.jsrt.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/segmentation/config/data/hrf/__init__.py b/src/mednet/segment/config/data/montgomery/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/hrf/__init__.py
rename to src/mednet/segment/config/data/montgomery/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/montgomery/datamodule.py b/src/mednet/segment/config/data/montgomery/datamodule.py
similarity index 92%
rename from src/mednet/libs/segmentation/config/data/montgomery/datamodule.py
rename to src/mednet/segment/config/data/montgomery/datamodule.py
index 663f9371..25d642fb 100644
--- a/src/mednet/libs/segmentation/config/data/montgomery/datamodule.py
+++ b/src/mednet/segment/config/data/montgomery/datamodule.py
@@ -10,16 +10,15 @@ import numpy as np
import PIL.Image
import pkg_resources
import torch
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -127,4 +126,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/montgomery/default.json b/src/mednet/segment/config/data/montgomery/default.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/montgomery/default.json
rename to src/mednet/segment/config/data/montgomery/default.json
diff --git a/src/mednet/libs/segmentation/config/data/montgomery/default.py b/src/mednet/segment/config/data/montgomery/default.py
similarity index 75%
rename from src/mednet/libs/segmentation/config/data/montgomery/default.py
rename to src/mednet/segment/config/data/montgomery/default.py
index 40b1632a..a8326197 100644
--- a/src/mednet/libs/segmentation/config/data/montgomery/default.py
+++ b/src/mednet/segment/config/data/montgomery/default.py
@@ -7,8 +7,6 @@
* Split reference: [GAAL-2020]_
"""
-from mednet.libs.segmentation.config.data.montgomery.datamodule import (
- DataModule,
-)
+from mednet.segment.config.data.montgomery.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/segmentation/config/data/iostar/__init__.py b/src/mednet/segment/config/data/refuge/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/iostar/__init__.py
rename to src/mednet/segment/config/data/refuge/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/refuge/cup.py b/src/mednet/segment/config/data/refuge/cup.py
similarity index 79%
rename from src/mednet/libs/segmentation/config/data/refuge/cup.py
rename to src/mednet/segment/config/data/refuge/cup.py
index bf4a5264..38b7a5d3 100644
--- a/src/mednet/libs/segmentation/config/data/refuge/cup.py
+++ b/src/mednet/segment/config/data/refuge/cup.py
@@ -6,6 +6,6 @@
* Reference (including split): [REFUGE-2018]_
"""
-from mednet.libs.segmentation.config.data.refuge.datamodule import DataModule
+from mednet.segment.config.data.refuge.datamodule import DataModule
datamodule = DataModule("default.json", target_type="cup")
diff --git a/src/mednet/libs/segmentation/config/data/refuge/datamodule.py b/src/mednet/segment/config/data/refuge/datamodule.py
similarity index 91%
rename from src/mednet/libs/segmentation/config/data/refuge/datamodule.py
rename to src/mednet/segment/config/data/refuge/datamodule.py
index 696a204e..b4eb11f4 100644
--- a/src/mednet/libs/segmentation/config/data/refuge/datamodule.py
+++ b/src/mednet/segment/config/data/refuge/datamodule.py
@@ -8,17 +8,16 @@ import pathlib
import PIL.Image
import pkg_resources
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -141,4 +140,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(target_type),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/refuge/default.json b/src/mednet/segment/config/data/refuge/default.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/default.json
rename to src/mednet/segment/config/data/refuge/default.json
diff --git a/src/mednet/libs/segmentation/config/data/refuge/disc.py b/src/mednet/segment/config/data/refuge/disc.py
similarity index 80%
rename from src/mednet/libs/segmentation/config/data/refuge/disc.py
rename to src/mednet/segment/config/data/refuge/disc.py
index 3c876e7e..357418ba 100644
--- a/src/mednet/libs/segmentation/config/data/refuge/disc.py
+++ b/src/mednet/segment/config/data/refuge/disc.py
@@ -6,6 +6,6 @@
* Reference (including split): [REFUGE-2018]_
"""
-from mednet.libs.segmentation.config.data.refuge.datamodule import DataModule
+from mednet.segment.config.data.refuge.datamodule import DataModule
datamodule = DataModule("default.json", target_type="disc")
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0001.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0001.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0001.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0001.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0002.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0002.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0002.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0002.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0003.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0003.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0003.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0003.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0004.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0004.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0004.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0004.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0005.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0005.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0005.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0005.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0006.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0006.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0006.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0006.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0007.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0007.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0007.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0007.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0008.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0008.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0008.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0008.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0009.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0009.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0009.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0009.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0010.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0010.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0010.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0010.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0011.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0011.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0011.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0011.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0012.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0012.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0012.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0012.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0013.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0013.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0013.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0013.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0014.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0014.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0014.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0014.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0015.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0015.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0015.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0015.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0016.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0016.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0016.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0016.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0017.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0017.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0017.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0017.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0018.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0018.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0018.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0018.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0019.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0019.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0019.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0019.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0020.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0020.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0020.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0020.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0021.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0021.png
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rename from src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0021.png
rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0021.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/REFUGE-Validation400/V0022.png b/src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0022.png
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rename to src/mednet/segment/config/data/refuge/masks/REFUGE-Validation400/V0022.png
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diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0339.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0339.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0339.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0339.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0340.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0340.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0340.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0340.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0341.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0341.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0341.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0341.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0342.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0342.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0342.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0342.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0343.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0343.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0343.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0343.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0344.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0344.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0344.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0344.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0345.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0345.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0345.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0345.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0346.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0346.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0346.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0346.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0347.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0347.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0347.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0347.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0348.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0348.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0348.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0348.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0349.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0349.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0349.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0349.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0350.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0350.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0350.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0350.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0351.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0351.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0351.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0351.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0352.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0352.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0352.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0352.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0353.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0353.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0353.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0353.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0354.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0354.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0354.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0354.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0355.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0355.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0355.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0355.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0356.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0356.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0356.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0356.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0357.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0357.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0357.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0357.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0358.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0358.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0358.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0358.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0359.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0359.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0359.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0359.png
diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0360.png b/src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0360.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/masks/Training400/Non-Glaucoma/n0360.png
rename to src/mednet/segment/config/data/refuge/masks/Training400/Non-Glaucoma/n0360.png
diff --git a/src/mednet/libs/segmentation/config/data/jsrt/__init__.py b/src/mednet/segment/config/data/rimoner3/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/jsrt/__init__.py
rename to src/mednet/segment/config/data/rimoner3/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/cup_exp1.py b/src/mednet/segment/config/data/rimoner3/cup_exp1.py
similarity index 78%
rename from src/mednet/libs/segmentation/config/data/rimoner3/cup_exp1.py
rename to src/mednet/segment/config/data/rimoner3/cup_exp1.py
index 19ed62d0..3c13457d 100644
--- a/src/mednet/libs/segmentation/config/data/rimoner3/cup_exp1.py
+++ b/src/mednet/segment/config/data/rimoner3/cup_exp1.py
@@ -6,6 +6,6 @@
* Split reference: [MANINIS-2016]_
"""
-from mednet.libs.segmentation.config.data.rimoner3.datamodule import DataModule
+from mednet.segment.config.data.rimoner3.datamodule import DataModule
datamodule = DataModule("optic-cup-exp1.json")
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/cup_exp2.py b/src/mednet/segment/config/data/rimoner3/cup_exp2.py
similarity index 78%
rename from src/mednet/libs/segmentation/config/data/rimoner3/cup_exp2.py
rename to src/mednet/segment/config/data/rimoner3/cup_exp2.py
index 19ed62d0..3c13457d 100644
--- a/src/mednet/libs/segmentation/config/data/rimoner3/cup_exp2.py
+++ b/src/mednet/segment/config/data/rimoner3/cup_exp2.py
@@ -6,6 +6,6 @@
* Split reference: [MANINIS-2016]_
"""
-from mednet.libs.segmentation.config.data.rimoner3.datamodule import DataModule
+from mednet.segment.config.data.rimoner3.datamodule import DataModule
datamodule = DataModule("optic-cup-exp1.json")
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/datamodule.py b/src/mednet/segment/config/data/rimoner3/datamodule.py
similarity index 91%
rename from src/mednet/libs/segmentation/config/data/rimoner3/datamodule.py
rename to src/mednet/segment/config/data/rimoner3/datamodule.py
index 81574441..705692e5 100644
--- a/src/mednet/libs/segmentation/config/data/rimoner3/datamodule.py
+++ b/src/mednet/segment/config/data/rimoner3/datamodule.py
@@ -8,16 +8,15 @@ import pathlib
import PIL.Image
import pkg_resources
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import crop, to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -113,4 +112,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/disc_exp1.py b/src/mednet/segment/config/data/rimoner3/disc_exp1.py
similarity index 78%
rename from src/mednet/libs/segmentation/config/data/rimoner3/disc_exp1.py
rename to src/mednet/segment/config/data/rimoner3/disc_exp1.py
index 19c1cb09..9298ae34 100644
--- a/src/mednet/libs/segmentation/config/data/rimoner3/disc_exp1.py
+++ b/src/mednet/segment/config/data/rimoner3/disc_exp1.py
@@ -6,6 +6,6 @@
* Split reference: [MANINIS-2016]_
"""
-from mednet.libs.segmentation.config.data.rimoner3.datamodule import DataModule
+from mednet.segment.config.data.rimoner3.datamodule import DataModule
datamodule = DataModule("optic-disc-exp1.json")
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/disc_exp2.py b/src/mednet/segment/config/data/rimoner3/disc_exp2.py
similarity index 78%
rename from src/mednet/libs/segmentation/config/data/rimoner3/disc_exp2.py
rename to src/mednet/segment/config/data/rimoner3/disc_exp2.py
index bb17c246..bd1547ae 100644
--- a/src/mednet/libs/segmentation/config/data/rimoner3/disc_exp2.py
+++ b/src/mednet/segment/config/data/rimoner3/disc_exp2.py
@@ -6,6 +6,6 @@
* Split reference: [MANINIS-2016]_
"""
-from mednet.libs.segmentation.config.data.rimoner3.datamodule import DataModule
+from mednet.segment.config.data.rimoner3.datamodule import DataModule
datamodule = DataModule("optic-disc-exp2.json")
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-1-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-1-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-1-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-1-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-10-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-10-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-10-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-10-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-11-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-11-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-11-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-11-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-12-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-12-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-12-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-12-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-13-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-13-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-13-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-13-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-14-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-14-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-14-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-14-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-15-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-15-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-15-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-15-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-16-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-16-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-16-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-16-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-17-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-17-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-17-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-17-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-18-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-18-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-18-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-18-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-19-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-19-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-19-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-19-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-2-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-2-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-2-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-2-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-20-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-20-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-20-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-20-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-21-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-21-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-21-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-21-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-22-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-22-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-22-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-22-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-23-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-23-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-23-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-23-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-24-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-24-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-24-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-24-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-25-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-25-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-25-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-25-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-26-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-26-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-26-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-26-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Glaucoma and suspects/G-27-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Glaucoma and suspects/G-27-R.jpg
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rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-63-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-63-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-64-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-64-R.jpg
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rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-64-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-64-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-65-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-65-L.jpg
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diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-68-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-68-R.jpg
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rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-68-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-69-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-69-L.jpg
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rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-69-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-69-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-7-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-7-L.jpg
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rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-7-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-7-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-70-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-70-R.jpg
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rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-70-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-70-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-71-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-71-L.jpg
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rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-71-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-71-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-72-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-72-R.jpg
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diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-73-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-73-R.jpg
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diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-74-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-74-L.jpg
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rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-74-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-75-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-75-R.jpg
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rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-75-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-76-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-76-R.jpg
similarity index 100%
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rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-76-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-78-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-78-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-78-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-78-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-79-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-79-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-79-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-79-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-8-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-8-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-8-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-8-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-80-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-80-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-80-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-80-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-81-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-81-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-81-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-81-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-82-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-82-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-82-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-82-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-83-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-83-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-83-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-83-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-84-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-84-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-84-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-84-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-85-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-85-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-85-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-85-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-86-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-86-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-86-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-86-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-87-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-87-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-87-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-87-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-88-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-88-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-88-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-88-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-9-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-9-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-9-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-9-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-90-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-90-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-90-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-90-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-91-L.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-91-L.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-91-L.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-91-L.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-92-R.jpg b/src/mednet/segment/config/data/rimoner3/masks/Healthy/N-92-R.jpg
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/masks/Healthy/N-92-R.jpg
rename to src/mednet/segment/config/data/rimoner3/masks/Healthy/N-92-R.jpg
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/optic-cup-avg.json b/src/mednet/segment/config/data/rimoner3/optic-cup-avg.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/optic-cup-avg.json
rename to src/mednet/segment/config/data/rimoner3/optic-cup-avg.json
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/optic-cup-exp1.json b/src/mednet/segment/config/data/rimoner3/optic-cup-exp1.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/optic-cup-exp1.json
rename to src/mednet/segment/config/data/rimoner3/optic-cup-exp1.json
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/optic-cup-exp2.json b/src/mednet/segment/config/data/rimoner3/optic-cup-exp2.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/optic-cup-exp2.json
rename to src/mednet/segment/config/data/rimoner3/optic-cup-exp2.json
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/optic-disc-avg.json b/src/mednet/segment/config/data/rimoner3/optic-disc-avg.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/optic-disc-avg.json
rename to src/mednet/segment/config/data/rimoner3/optic-disc-avg.json
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/optic-disc-exp1.json b/src/mednet/segment/config/data/rimoner3/optic-disc-exp1.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/optic-disc-exp1.json
rename to src/mednet/segment/config/data/rimoner3/optic-disc-exp1.json
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/optic-disc-exp2.json b/src/mednet/segment/config/data/rimoner3/optic-disc-exp2.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/optic-disc-exp2.json
rename to src/mednet/segment/config/data/rimoner3/optic-disc-exp2.json
diff --git a/src/mednet/libs/segmentation/config/data/montgomery/__init__.py b/src/mednet/segment/config/data/shenzhen/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/montgomery/__init__.py
rename to src/mednet/segment/config/data/shenzhen/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/shenzhen/datamodule.py b/src/mednet/segment/config/data/shenzhen/datamodule.py
similarity index 88%
rename from src/mednet/libs/segmentation/config/data/shenzhen/datamodule.py
rename to src/mednet/segment/config/data/shenzhen/datamodule.py
index a65f3239..cb5e9256 100644
--- a/src/mednet/libs/segmentation/config/data/shenzhen/datamodule.py
+++ b/src/mednet/segment/config/data/shenzhen/datamodule.py
@@ -8,17 +8,16 @@ import pathlib
import PIL.Image
import torch
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -96,4 +95,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/shenzhen/default.json b/src/mednet/segment/config/data/shenzhen/default.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/shenzhen/default.json
rename to src/mednet/segment/config/data/shenzhen/default.json
diff --git a/src/mednet/libs/segmentation/config/data/shenzhen/default.py b/src/mednet/segment/config/data/shenzhen/default.py
similarity index 77%
rename from src/mednet/libs/segmentation/config/data/shenzhen/default.py
rename to src/mednet/segment/config/data/shenzhen/default.py
index c66e34ad..8089a678 100644
--- a/src/mednet/libs/segmentation/config/data/shenzhen/default.py
+++ b/src/mednet/segment/config/data/shenzhen/default.py
@@ -6,6 +6,6 @@
* Split reference: [GAAL-2020]_
"""
-from mednet.libs.segmentation.config.data.shenzhen.datamodule import DataModule
+from mednet.segment.config.data.shenzhen.datamodule import DataModule
datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/segmentation/config/data/refuge/__init__.py b/src/mednet/segment/config/data/stare/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/refuge/__init__.py
rename to src/mednet/segment/config/data/stare/__init__.py
diff --git a/src/mednet/libs/segmentation/config/data/stare/ah.json b/src/mednet/segment/config/data/stare/ah.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/ah.json
rename to src/mednet/segment/config/data/stare/ah.json
diff --git a/src/mednet/libs/segmentation/config/data/stare/ah.py b/src/mednet/segment/config/data/stare/ah.py
similarity index 81%
rename from src/mednet/libs/segmentation/config/data/stare/ah.py
rename to src/mednet/segment/config/data/stare/ah.py
index 1bde293d..c9f29fd5 100644
--- a/src/mednet/libs/segmentation/config/data/stare/ah.py
+++ b/src/mednet/segment/config/data/stare/ah.py
@@ -8,6 +8,6 @@
* This dataset offers a second-annotator comparison (using protocol "vk")
"""
-from mednet.libs.segmentation.config.data.stare.datamodule import DataModule
+from mednet.segment.config.data.stare.datamodule import DataModule
datamodule = DataModule("ah.json")
diff --git a/src/mednet/libs/segmentation/config/data/stare/datamodule.py b/src/mednet/segment/config/data/stare/datamodule.py
similarity index 89%
rename from src/mednet/libs/segmentation/config/data/stare/datamodule.py
rename to src/mednet/segment/config/data/stare/datamodule.py
index 06bceb50..e8216f7b 100644
--- a/src/mednet/libs/segmentation/config/data/stare/datamodule.py
+++ b/src/mednet/segment/config/data/stare/datamodule.py
@@ -8,17 +8,16 @@ import pathlib
import PIL.Image
import pkg_resources
-from mednet.libs.common.data.datamodule import CachingDataModule
-from mednet.libs.common.data.split import make_split
-from mednet.libs.common.models.transforms import crop_image_to_mask
-from mednet.libs.common.utils.rc import load_rc
-from mednet.libs.segmentation.data.typing import Sample
-from mednet.libs.segmentation.data.typing import (
- SegmentationRawDataLoader as _SegmentationRawDataLoader,
-)
from torchvision import tv_tensors
from torchvision.transforms.functional import to_tensor
+from .....data.datamodule import CachingDataModule
+from .....data.split import make_split
+from .....models.transforms import crop_image_to_mask
+from .....utils.rc import load_rc
+from ....data.typing import Sample
+from ....data.typing import SegmentationRawDataLoader as _SegmentationRawDataLoader
+
CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
"""Key to search for in the configuration file for the root directory of this
database."""
@@ -106,4 +105,5 @@ class DataModule(CachingDataModule):
raw_data_loader=SegmentationRawDataLoader(),
database_name=__package__.rsplit(".", 1)[1],
split_name=pathlib.Path(split_filename).stem,
+ task="segmentation",
)
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0001.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0001.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0001.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0001.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0002.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0002.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0002.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0002.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0003.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0003.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0003.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0003.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0004.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0004.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0004.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0004.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0005.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0005.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0005.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0005.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0044.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0044.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0044.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0044.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0077.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0077.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0077.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0077.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0081.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0081.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0081.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0081.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0082.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0082.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0082.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0082.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0139.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0139.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0139.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0139.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0162.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0162.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0162.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0162.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0163.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0163.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0163.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0163.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0235.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0235.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0235.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0235.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0236.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0236.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0236.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0236.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0239.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0239.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0239.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0239.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0240.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0240.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0240.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0240.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0255.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0255.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0255.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0255.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0291.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0291.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0291.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0291.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0319.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0319.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0319.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0319.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0324.png b/src/mednet/segment/config/data/stare/masks/stare-images/im0324.png
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/masks/stare-images/im0324.png
rename to src/mednet/segment/config/data/stare/masks/stare-images/im0324.png
diff --git a/src/mednet/libs/segmentation/config/data/stare/vk.json b/src/mednet/segment/config/data/stare/vk.json
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/vk.json
rename to src/mednet/segment/config/data/stare/vk.json
diff --git a/src/mednet/libs/segmentation/config/data/stare/vk.py b/src/mednet/segment/config/data/stare/vk.py
similarity index 81%
rename from src/mednet/libs/segmentation/config/data/stare/vk.py
rename to src/mednet/segment/config/data/stare/vk.py
index 2084c8eb..58255970 100644
--- a/src/mednet/libs/segmentation/config/data/stare/vk.py
+++ b/src/mednet/segment/config/data/stare/vk.py
@@ -8,6 +8,6 @@
* This dataset offers a second-annotator comparison (using protocol "ah")
"""
-from mednet.libs.segmentation.config.data.stare.datamodule import DataModule
+from mednet.segment.config.data.stare.datamodule import DataModule
datamodule = DataModule("vk.json")
diff --git a/src/mednet/libs/segmentation/config/data/rimoner3/__init__.py b/src/mednet/segment/config/models/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/rimoner3/__init__.py
rename to src/mednet/segment/config/models/__init__.py
diff --git a/src/mednet/libs/segmentation/config/models/driu.py b/src/mednet/segment/config/models/driu.py
similarity index 65%
rename from src/mednet/libs/segmentation/config/models/driu.py
rename to src/mednet/segment/config/models/driu.py
index 153691b0..2c0ff44e 100644
--- a/src/mednet/libs/segmentation/config/models/driu.py
+++ b/src/mednet/segment/config/models/driu.py
@@ -11,21 +11,22 @@ deep Convolutional Neural Networks (CNNs).
Reference: [MANINIS-2016]_
"""
-import mednet.libs.common.models.transforms
-import mednet.libs.segmentation.models.driu
-import mednet.libs.segmentation.models.losses
import torch.optim
import torchvision.transforms
-model = mednet.libs.segmentation.models.driu.DRIU(
- loss_type=mednet.libs.segmentation.models.losses.SoftJaccardBCELogitsLoss,
+import mednet.models.transforms
+import mednet.segment.models.driu
+import mednet.segment.models.losses
+
+model = mednet.segment.models.driu.DRIU(
+ loss_type=mednet.segment.models.losses.SoftJaccardBCELogitsLoss,
loss_arguments=dict(alpha=0.7), # 0.7 BCE + 0.3 Jaccard
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.01),
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
pretrained=False,
)
diff --git a/src/mednet/libs/segmentation/config/models/driu_bn.py b/src/mednet/segment/config/models/driu_bn.py
similarity index 65%
rename from src/mednet/libs/segmentation/config/models/driu_bn.py
rename to src/mednet/segment/config/models/driu_bn.py
index 96656a1c..0ea17bec 100644
--- a/src/mednet/libs/segmentation/config/models/driu_bn.py
+++ b/src/mednet/segment/config/models/driu_bn.py
@@ -11,21 +11,22 @@ deep Convolutional Neural Networks (CNNs).
Reference: [MANINIS-2016]_
"""
-import mednet.libs.common.models.transforms
-import mednet.libs.segmentation.models.driu_bn
-import mednet.libs.segmentation.models.losses
import torch.optim
import torchvision.transforms
-model = mednet.libs.segmentation.models.driu_bn.DRIUBN(
- loss_type=mednet.libs.segmentation.models.losses.SoftJaccardBCELogitsLoss,
+import mednet.models.transforms
+import mednet.segment.models.driu_bn
+import mednet.segment.models.losses
+
+model = mednet.segment.models.driu_bn.DRIUBN(
+ loss_type=mednet.segment.models.losses.SoftJaccardBCELogitsLoss,
loss_arguments=dict(alpha=0.7), # 0.7 BCE + 0.3 Jaccard
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.01),
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
pretrained=False,
)
diff --git a/src/mednet/libs/segmentation/config/models/driu_od.py b/src/mednet/segment/config/models/driu_od.py
similarity index 64%
rename from src/mednet/libs/segmentation/config/models/driu_od.py
rename to src/mednet/segment/config/models/driu_od.py
index 47e865a6..c1089eec 100644
--- a/src/mednet/libs/segmentation/config/models/driu_od.py
+++ b/src/mednet/segment/config/models/driu_od.py
@@ -11,21 +11,22 @@ deep Convolutional Neural Networks (CNNs).
Reference: [MANINIS-2016]_
"""
-import mednet.libs.common.models.transforms
-import mednet.libs.segmentation.models.driu_od
-import mednet.libs.segmentation.models.losses
import torch.optim
import torchvision.transforms
-model = mednet.libs.segmentation.models.driu_od.DRIUOD(
- loss_type=mednet.libs.segmentation.models.losses.SoftJaccardBCELogitsLoss,
+import mednet.models.transforms
+import mednet.segment.models.driu_od
+import mednet.segment.models.losses
+
+model = mednet.segment.models.driu_od.DRIUOD(
+ loss_type=mednet.segment.models.losses.SoftJaccardBCELogitsLoss,
loss_arguments=dict(alpha=0.7), # 0.7 BCE + 0.3 Jaccard
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.01),
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
pretrained=False,
)
diff --git a/src/mednet/libs/segmentation/config/models/driu_pix.py b/src/mednet/segment/config/models/driu_pix.py
similarity index 64%
rename from src/mednet/libs/segmentation/config/models/driu_pix.py
rename to src/mednet/segment/config/models/driu_pix.py
index 1d29213c..4c5fab43 100644
--- a/src/mednet/libs/segmentation/config/models/driu_pix.py
+++ b/src/mednet/segment/config/models/driu_pix.py
@@ -11,21 +11,22 @@ deep Convolutional Neural Networks (CNNs).
Reference: [MANINIS-2016]_
"""
-import mednet.libs.common.models.transforms
-import mednet.libs.segmentation.models.driu_pix
-import mednet.libs.segmentation.models.losses
import torch.optim
import torchvision.transforms
-model = mednet.libs.segmentation.models.driu_pix.DRIUPix(
- loss_type=mednet.libs.segmentation.models.losses.SoftJaccardBCELogitsLoss,
+import mednet.models.transforms
+import mednet.segment.models.driu_pix
+import mednet.segment.models.losses
+
+model = mednet.segment.models.driu_pix.DRIUPix(
+ loss_type=mednet.segment.models.losses.SoftJaccardBCELogitsLoss,
loss_arguments=dict(alpha=0.7), # 0.7 BCE + 0.3 Jaccard
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.01),
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
pretrained=False,
)
diff --git a/src/mednet/libs/segmentation/config/models/hed.py b/src/mednet/segment/config/models/hed.py
similarity index 56%
rename from src/mednet/libs/segmentation/config/models/hed.py
rename to src/mednet/segment/config/models/hed.py
index c2cbe04e..e251f405 100644
--- a/src/mednet/libs/segmentation/config/models/hed.py
+++ b/src/mednet/segment/config/models/hed.py
@@ -7,21 +7,22 @@
Reference: [XIE-2015]_
"""
-import mednet.libs.common.models.transforms
-import mednet.libs.segmentation.models.hed
-import mednet.libs.segmentation.models.losses
import torch.optim
import torchvision.transforms
-model = mednet.libs.segmentation.models.hed.HED(
- loss_type=mednet.libs.segmentation.models.losses.MultiSoftJaccardBCELogitsLoss,
+import mednet.models.transforms
+import mednet.segment.models.hed
+import mednet.segment.models.losses
+
+model = mednet.segment.models.hed.HED(
+ loss_type=mednet.segment.models.losses.MultiSoftJaccardBCELogitsLoss,
loss_arguments=dict(alpha=0.7), # 0.7 BCE + 0.3 Jaccard
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.01),
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
pretrained=False,
)
diff --git a/src/mednet/libs/segmentation/config/models/lwnet.py b/src/mednet/segment/config/models/lwnet.py
similarity index 71%
rename from src/mednet/libs/segmentation/config/models/lwnet.py
rename to src/mednet/segment/config/models/lwnet.py
index 94bc9768..dd9d185f 100644
--- a/src/mednet/libs/segmentation/config/models/lwnet.py
+++ b/src/mednet/segment/config/models/lwnet.py
@@ -9,29 +9,30 @@ closely matches (or outperforms) other more complex techniques.
Reference: [GALDRAN-2020]_
"""
-import mednet.libs.common.models.transforms
-import mednet.libs.segmentation.models.losses
-import mednet.libs.segmentation.models.lwnet
import torch.optim
import torch.optim.lr_scheduler
import torchvision.transforms
+import mednet.models.transforms
+import mednet.segment.models.losses
+import mednet.segment.models.lwnet
+
max_lr = 0.01 # start
min_lr = 1e-08 # valley
# Original strategy: https://github.com/agaldran/lwnet/blob/master/train_cyclical.py#L298
# About 20 * len(train-data-loader)
cycle = 100 # 1/2 epochs for a complete scheduling cycle
-model = mednet.libs.segmentation.models.lwnet.LittleWNet(
- loss_type=mednet.libs.segmentation.models.losses.MultiWeightedBCELogitsLoss,
+model = mednet.segment.models.lwnet.LittleWNet(
+ loss_type=mednet.segment.models.losses.MultiWeightedBCELogitsLoss,
loss_arguments=dict(),
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=max_lr),
scheduler_type=torch.optim.lr_scheduler.CosineAnnealingLR,
scheduler_arguments=dict(T_max=cycle, eta_min=min_lr),
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
)
diff --git a/src/mednet/libs/segmentation/config/models/m2unet.py b/src/mednet/segment/config/models/m2unet.py
similarity index 73%
rename from src/mednet/libs/segmentation/config/models/m2unet.py
rename to src/mednet/segment/config/models/m2unet.py
index 676fbfa9..050d56f6 100644
--- a/src/mednet/libs/segmentation/config/models/m2unet.py
+++ b/src/mednet/segment/config/models/m2unet.py
@@ -15,21 +15,22 @@ segmentation applications and the speed of MobileNetV2 networks.
References: [SANDLER-2018]_, [RONNEBERGER-2015]_
"""
-import mednet.libs.common.models.transforms
-import mednet.libs.segmentation.models.losses
-import mednet.libs.segmentation.models.m2unet
import torch.optim
import torchvision.transforms
-model = mednet.libs.segmentation.models.m2unet.M2Unet(
- loss_type=mednet.libs.segmentation.models.losses.SoftJaccardBCELogitsLoss,
+import mednet.models.transforms
+import mednet.segment.models.losses
+import mednet.segment.models.m2unet
+
+model = mednet.segment.models.m2unet.M2Unet(
+ loss_type=mednet.segment.models.losses.SoftJaccardBCELogitsLoss,
loss_arguments=dict(alpha=0.7), # 0.7 BCE + 0.3 Jaccard
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.01),
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
pretrained=False,
)
diff --git a/src/mednet/libs/segmentation/config/models/unet.py b/src/mednet/segment/config/models/unet.py
similarity index 69%
rename from src/mednet/libs/segmentation/config/models/unet.py
rename to src/mednet/segment/config/models/unet.py
index d215fa66..6a66ea9e 100644
--- a/src/mednet/libs/segmentation/config/models/unet.py
+++ b/src/mednet/segment/config/models/unet.py
@@ -13,21 +13,22 @@ to yield more precise segmentations.
Reference: [RONNEBERGER-2015]_
"""
-import mednet.libs.common.models.transforms
-import mednet.libs.segmentation.models.losses
-import mednet.libs.segmentation.models.unet
import torch.optim
import torchvision.transforms
-model = mednet.libs.segmentation.models.unet.Unet(
- loss_type=mednet.libs.segmentation.models.losses.SoftJaccardBCELogitsLoss,
+import mednet.models.transforms
+import mednet.segment.models.losses
+import mednet.segment.models.unet
+
+model = mednet.segment.models.unet.Unet(
+ loss_type=mednet.segment.models.losses.SoftJaccardBCELogitsLoss,
loss_arguments=dict(alpha=0.7), # 0.7 BCE + 0.3 Jaccard
optimizer_type=torch.optim.Adam,
optimizer_arguments=dict(lr=0.01),
model_transforms=[
- mednet.libs.common.models.transforms.SquareCenterPad(),
+ mednet.models.transforms.SquareCenterPad(),
torchvision.transforms.Resize(512, antialias=True),
- mednet.libs.common.models.transforms.RGB(),
+ mednet.models.transforms.RGB(),
],
pretrained=False,
)
diff --git a/src/mednet/libs/segmentation/config/data/shenzhen/__init__.py b/src/mednet/segment/data/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/shenzhen/__init__.py
rename to src/mednet/segment/data/__init__.py
diff --git a/src/mednet/libs/segmentation/data/typing.py b/src/mednet/segment/data/typing.py
similarity index 75%
rename from src/mednet/libs/segmentation/data/typing.py
rename to src/mednet/segment/data/typing.py
index 8c24284b..727b55a2 100644
--- a/src/mednet/libs/segmentation/data/typing.py
+++ b/src/mednet/segment/data/typing.py
@@ -1,8 +1,15 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+"""Define specialized data typing for segmentation tasks."""
+
import typing
from typing import TypedDict
import torch
-from mednet.libs.common.data.typing import RawDataLoader
+
+from ...data.typing import RawDataLoader
class SegmentationData(TypedDict):
@@ -27,7 +34,7 @@ class SegmentationRawDataLoader(RawDataLoader):
Parameters
----------
- _
+ _
Information about the sample to load. Implementation dependent.
"""
diff --git a/src/mednet/libs/segmentation/config/data/stare/__init__.py b/src/mednet/segment/engine/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/data/stare/__init__.py
rename to src/mednet/segment/engine/__init__.py
diff --git a/src/mednet/libs/segmentation/engine/dumper.py b/src/mednet/segment/engine/dumper.py
similarity index 100%
rename from src/mednet/libs/segmentation/engine/dumper.py
rename to src/mednet/segment/engine/dumper.py
diff --git a/src/mednet/libs/segmentation/engine/evaluator.py b/src/mednet/segment/engine/evaluator.py
similarity index 97%
rename from src/mednet/libs/segmentation/engine/evaluator.py
rename to src/mednet/segment/engine/evaluator.py
index 027e876f..a74808f1 100644
--- a/src/mednet/libs/segmentation/engine/evaluator.py
+++ b/src/mednet/segment/engine/evaluator.py
@@ -590,10 +590,10 @@ def run(
* ``counts``: dictionary where keys are thresholds, and values are
sequence of integers containing the TP, FP, TN, FN (in this order).
- * ``auc_score``: a float indicating the area under the ROC curve
+ * ``roc_auc``: a float indicating the area under the ROC curve
for the split. It is calculated using a trapezoidal rule.
- * ``average_precision_score``: a float indicating the area under the
+ * ``average_precision``: a float indicating the area under the
precision-recall curve, calculated using a rectangle rule.
* ``curves``: dictionary with 2 keys:
@@ -652,13 +652,14 @@ def run(
] = 1.0
# populates data to be recorded in JSON format
+ eval_json_data.setdefault(split_name, {})["samples"] = len(samples)
eval_json_data.setdefault(split_name, {})["counts"] = {
k: v for k, v in zip(threshold_list, counts)
}
- eval_json_data.setdefault(split_name, {})["auc_score"] = (
+ eval_json_data.setdefault(split_name, {})["roc_auc"] = (
credible.curves.area_under_the_curve((fpr_curve, tpr_curve))
)
- eval_json_data.setdefault(split_name, {})["average_precision_score"] = (
+ eval_json_data.setdefault(split_name, {})["average_precision"] = (
credible.curves.average_metric((precision_curve, recall_curve))
)
eval_json_data.setdefault(split_name, {})["curves"] = dict(
@@ -711,6 +712,7 @@ def run(
base_metrics = all_metrics(
*(list(eval_json_data[split_name]["counts"].values())[threshold_index])
)
+ eval_json_data[split_name]["threshold"] = threshold_list[threshold_index]
eval_json_data[split_name].update(
{k: v for k, v in zip(metrics_available, base_metrics)}
)
@@ -744,15 +746,17 @@ def make_table(
# terminal-style table, format, and print to screen. Record the table into
# a file for later usage.
metrics_available = list(typing.get_args(SUPPORTED_METRIC_TYPE))
- table_headers = ["subset", "threshold"] + metrics_available + ["auroc", "avgprec"]
+ table_headers = (
+ ["subset", "samples", "threshold"] + metrics_available + ["auc_roc", "avg.prec"]
+ )
table_data = []
for split_name, data in eval_data.items():
base_metrics = [data[k] for k in metrics_available]
table_data.append(
- [split_name, threshold]
+ [split_name, data["samples"], threshold]
+ base_metrics
- + [data["auc_score"], data["average_precision_score"]]
+ + [data["roc_auc"], data["average_precision"]]
)
if "second_annotator" in data:
@@ -792,7 +796,7 @@ def make_plots(eval_data: dict[str, dict[str, typing.Any]]) -> list:
ax.plot(
data["curves"]["roc"]["fpr"],
data["curves"]["roc"]["tpr"],
- label=f"{split_name} (AUC: {data['auc_score']:.2f})",
+ label=f"{split_name} (AUC: {data['roc_auc']:.2f})",
)
if "second_annotator" in data:
@@ -817,7 +821,7 @@ def make_plots(eval_data: dict[str, dict[str, typing.Any]]) -> list:
ax.plot(
data["curves"]["precision_recall"]["recall"],
data["curves"]["precision_recall"]["precision"],
- label=f"{split_name} (AP: {data['average_precision_score']:.2f})",
+ label=f"{split_name} (AP: {data['average_precision']:.2f})",
)
if "second_annotator" in data:
diff --git a/src/mednet/libs/segmentation/engine/predictor.py b/src/mednet/segment/engine/predictor.py
similarity index 99%
rename from src/mednet/libs/segmentation/engine/predictor.py
rename to src/mednet/segment/engine/predictor.py
index a7fb4e14..882febfa 100644
--- a/src/mednet/libs/segmentation/engine/predictor.py
+++ b/src/mednet/segment/engine/predictor.py
@@ -11,7 +11,8 @@ import lightning.pytorch
import lightning.pytorch.callbacks
import torch.utils.data
import tqdm
-from mednet.libs.common.engine.device import DeviceManager
+
+from ...engine.device import DeviceManager
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/segmentation/engine/viewer.py b/src/mednet/segment/engine/viewer.py
similarity index 100%
rename from src/mednet/libs/segmentation/engine/viewer.py
rename to src/mednet/segment/engine/viewer.py
diff --git a/src/mednet/libs/segmentation/config/models/__init__.py b/src/mednet/segment/models/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/config/models/__init__.py
rename to src/mednet/segment/models/__init__.py
diff --git a/src/mednet/libs/segmentation/data/__init__.py b/src/mednet/segment/models/backbones/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/data/__init__.py
rename to src/mednet/segment/models/backbones/__init__.py
diff --git a/src/mednet/libs/segmentation/models/backbones/mobilenetv2.py b/src/mednet/segment/models/backbones/mobilenetv2.py
similarity index 100%
rename from src/mednet/libs/segmentation/models/backbones/mobilenetv2.py
rename to src/mednet/segment/models/backbones/mobilenetv2.py
diff --git a/src/mednet/libs/segmentation/models/backbones/vgg.py b/src/mednet/segment/models/backbones/vgg.py
similarity index 100%
rename from src/mednet/libs/segmentation/models/backbones/vgg.py
rename to src/mednet/segment/models/backbones/vgg.py
diff --git a/src/mednet/libs/segmentation/models/driu.py b/src/mednet/segment/models/driu.py
similarity index 98%
rename from src/mednet/libs/segmentation/models/driu.py
rename to src/mednet/segment/models/driu.py
index 40d09709..db8293f1 100644
--- a/src/mednet/libs/segmentation/models/driu.py
+++ b/src/mednet/segment/models/driu.py
@@ -9,8 +9,8 @@ import typing
import torch
import torch.nn
import torch.utils.data
-from mednet.libs.common.data.typing import TransformSequence
+from ...data.typing import TransformSequence
from .backbones.vgg import vgg16_for_segmentation
from .losses import SoftJaccardBCELogitsLoss
from .make_layers import UpsampleCropBlock, conv_with_kaiming_uniform
diff --git a/src/mednet/libs/segmentation/models/driu_bn.py b/src/mednet/segment/models/driu_bn.py
similarity index 98%
rename from src/mednet/libs/segmentation/models/driu_bn.py
rename to src/mednet/segment/models/driu_bn.py
index 9e32925e..cce925d0 100644
--- a/src/mednet/libs/segmentation/models/driu_bn.py
+++ b/src/mednet/segment/models/driu_bn.py
@@ -9,8 +9,8 @@ import typing
import torch
import torch.nn
import torch.utils.data
-from mednet.libs.common.data.typing import TransformSequence
+from ...data.typing import TransformSequence
from .backbones.vgg import vgg16_for_segmentation
from .losses import SoftJaccardBCELogitsLoss
from .make_layers import UpsampleCropBlock, conv_with_kaiming_uniform
diff --git a/src/mednet/libs/segmentation/models/driu_od.py b/src/mednet/segment/models/driu_od.py
similarity index 98%
rename from src/mednet/libs/segmentation/models/driu_od.py
rename to src/mednet/segment/models/driu_od.py
index 2336869e..aed96d8a 100644
--- a/src/mednet/libs/segmentation/models/driu_od.py
+++ b/src/mednet/segment/models/driu_od.py
@@ -8,8 +8,8 @@ import typing
import torch
import torch.nn
-from mednet.libs.common.data.typing import TransformSequence
+from ...data.typing import TransformSequence
from .backbones.vgg import vgg16_for_segmentation
from .driu import ConcatFuseBlock
from .losses import SoftJaccardBCELogitsLoss
diff --git a/src/mednet/libs/segmentation/models/driu_pix.py b/src/mednet/segment/models/driu_pix.py
similarity index 98%
rename from src/mednet/libs/segmentation/models/driu_pix.py
rename to src/mednet/segment/models/driu_pix.py
index 42436fcc..529ec345 100644
--- a/src/mednet/libs/segmentation/models/driu_pix.py
+++ b/src/mednet/segment/models/driu_pix.py
@@ -9,8 +9,8 @@ import typing
import torch
import torch.nn
import torch.utils.data
-from mednet.libs.common.data.typing import TransformSequence
+from ...data.typing import TransformSequence
from .backbones.vgg import vgg16_for_segmentation
from .driu import ConcatFuseBlock
from .losses import SoftJaccardBCELogitsLoss
diff --git a/src/mednet/libs/segmentation/models/hed.py b/src/mednet/segment/models/hed.py
similarity index 98%
rename from src/mednet/libs/segmentation/models/hed.py
rename to src/mednet/segment/models/hed.py
index cd99707d..3ef4f526 100644
--- a/src/mednet/libs/segmentation/models/hed.py
+++ b/src/mednet/segment/models/hed.py
@@ -8,8 +8,8 @@ import typing
import torch
import torch.nn
import torch.utils.data
-from mednet.libs.common.data.typing import TransformSequence
+from ...data.typing import TransformSequence
from .backbones.vgg import vgg16_for_segmentation
from .losses import MultiSoftJaccardBCELogitsLoss
from .make_layers import UpsampleCropBlock, conv_with_kaiming_uniform
diff --git a/src/mednet/libs/segmentation/models/losses.py b/src/mednet/segment/models/losses.py
similarity index 100%
rename from src/mednet/libs/segmentation/models/losses.py
rename to src/mednet/segment/models/losses.py
diff --git a/src/mednet/libs/segmentation/models/lwnet.py b/src/mednet/segment/models/lwnet.py
similarity index 98%
rename from src/mednet/libs/segmentation/models/lwnet.py
rename to src/mednet/segment/models/lwnet.py
index b2c0ac2f..8a677a8d 100644
--- a/src/mednet/libs/segmentation/models/lwnet.py
+++ b/src/mednet/segment/models/lwnet.py
@@ -20,9 +20,9 @@ import typing
import torch
import torch.nn
-from mednet.libs.common.data.typing import TransformSequence
-from mednet.libs.segmentation.models.losses import MultiWeightedBCELogitsLoss
+from ...data.typing import TransformSequence
+from ..models.losses import MultiWeightedBCELogitsLoss
from .segmentation_model import SegmentationModel
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/segmentation/models/m2unet.py b/src/mednet/segment/models/m2unet.py
similarity index 98%
rename from src/mednet/libs/segmentation/models/m2unet.py
rename to src/mednet/segment/models/m2unet.py
index 5734a2a4..c28d31f3 100644
--- a/src/mednet/libs/segmentation/models/m2unet.py
+++ b/src/mednet/segment/models/m2unet.py
@@ -8,10 +8,10 @@ import typing
import torch
import torch.nn
import torch.utils.data
-from mednet.libs.common.data.typing import TransformSequence
-from mednet.libs.segmentation.models.losses import SoftJaccardBCELogitsLoss
from torchvision.models.mobilenetv2 import InvertedResidual
+from ...data.typing import TransformSequence
+from ..models.losses import SoftJaccardBCELogitsLoss
from .backbones.mobilenetv2 import mobilenet_v2_for_segmentation
from .segmentation_model import SegmentationModel
diff --git a/src/mednet/libs/segmentation/models/make_layers.py b/src/mednet/segment/models/make_layers.py
similarity index 100%
rename from src/mednet/libs/segmentation/models/make_layers.py
rename to src/mednet/segment/models/make_layers.py
diff --git a/src/mednet/libs/segmentation/models/normalizer.py b/src/mednet/segment/models/normalizer.py
similarity index 100%
rename from src/mednet/libs/segmentation/models/normalizer.py
rename to src/mednet/segment/models/normalizer.py
diff --git a/src/mednet/libs/segmentation/models/segmentation_model.py b/src/mednet/segment/models/segmentation_model.py
similarity index 95%
rename from src/mednet/libs/segmentation/models/segmentation_model.py
rename to src/mednet/segment/models/segmentation_model.py
index 8f3c5f5e..a26a1fc3 100644
--- a/src/mednet/libs/segmentation/models/segmentation_model.py
+++ b/src/mednet/segment/models/segmentation_model.py
@@ -9,9 +9,10 @@ import torch
import torch.nn
import torch.optim.optimizer
import torch.utils.data
-from mednet.libs.common.data.typing import TransformSequence
-from mednet.libs.common.models.model import Model
-from mednet.libs.segmentation.models.losses import MultiWeightedBCELogitsLoss
+
+from ...data.typing import TransformSequence
+from ...models.model import Model
+from ..models.losses import MultiWeightedBCELogitsLoss
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/segmentation/models/unet.py b/src/mednet/segment/models/unet.py
similarity index 98%
rename from src/mednet/libs/segmentation/models/unet.py
rename to src/mednet/segment/models/unet.py
index f4d64f01..90dd50c2 100644
--- a/src/mednet/libs/segmentation/models/unet.py
+++ b/src/mednet/segment/models/unet.py
@@ -8,8 +8,8 @@ import typing
import torch.nn
import torch.utils.data
-from mednet.libs.common.data.typing import TransformSequence
+from ...data.typing import TransformSequence
from .backbones.vgg import vgg16_for_segmentation
from .losses import SoftJaccardBCELogitsLoss
from .make_layers import UnetBlock, conv_with_kaiming_uniform
diff --git a/src/mednet/libs/segmentation/engine/__init__.py b/src/mednet/segment/scripts/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/engine/__init__.py
rename to src/mednet/segment/scripts/__init__.py
diff --git a/src/mednet/segment/scripts/cli.py b/src/mednet/segment/scripts/cli.py
new file mode 100644
index 00000000..22966d2d
--- /dev/null
+++ b/src/mednet/segment/scripts/cli.py
@@ -0,0 +1,28 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import importlib
+
+import click
+from clapper.click import AliasedGroup
+
+
+@click.group(
+ cls=AliasedGroup,
+ context_settings=dict(help_option_names=["-?", "-h", "--help"]),
+)
+def segment():
+ """Image segmentation specialized commands."""
+ pass
+
+
+def _add_command(cli, module, obj):
+ cli.add_command(
+ getattr(importlib.import_module("." + module, package=__name__), obj)
+ )
+
+
+_add_command(segment, ".evaluate", "evaluate")
+_add_command(segment, ".view", "view")
+_add_command(segment, ".dump_annotations", "dump_annotations")
diff --git a/src/mednet/libs/segmentation/scripts/dump_annotations.py b/src/mednet/segment/scripts/dump_annotations.py
similarity index 79%
rename from src/mednet/libs/segmentation/scripts/dump_annotations.py
rename to src/mednet/segment/scripts/dump_annotations.py
index 5ee47567..247fded6 100644
--- a/src/mednet/libs/segmentation/scripts/dump_annotations.py
+++ b/src/mednet/segment/scripts/dump_annotations.py
@@ -7,7 +7,8 @@ import pathlib
import clapper.click
import clapper.logging
import click
-import mednet.libs.common.scripts.click
+
+from ...scripts.click import ConfigCommand
logger = clapper.logging.setup(
__name__.split(".")[0], format="%(levelname)s: %(message)s"
@@ -15,8 +16,8 @@ logger = clapper.logging.setup(
@click.command(
- entry_point_group="mednet.libs.segmentation.config",
- cls=mednet.libs.common.scripts.click.ConfigCommand,
+ entry_point_group="mednet.config",
+ cls=ConfigCommand,
epilog="""Examples:
1. Dump annotations for a dataset after pre-processing on a particular directory:
@@ -67,16 +68,19 @@ def dump_annotations(
) -> None: # numpydoc ignore=PR01
"""Dump annotations in a given folder, after pre-processing."""
- from mednet.libs.common.scripts.predict import (
- setup_datamodule,
- )
- from mednet.libs.common.scripts.utils import (
- save_json_metadata,
- save_json_with_backup,
- )
- from mednet.libs.segmentation.engine.dumper import run
+ from ...engine.trainer import validate_model_datamodule
+ from ...scripts.utils import save_json_metadata, save_json_with_backup
+ from ..engine.dumper import run
+
+ validate_model_datamodule(model, datamodule)
+ assert datamodule.task == "segmentation"
- setup_datamodule(datamodule, model, batch_size=1, parallel=-1)
+ # sets-up the data module
+ datamodule.model_transforms = list(model.model_transforms)
+ datamodule.batch_size = 1
+ datamodule.parallel = -1
+ datamodule.prepare_data()
+ datamodule.setup(stage="predict")
# stores all information we can think of, to reproduce this later
save_json_metadata(
diff --git a/src/mednet/libs/segmentation/scripts/evaluate.py b/src/mednet/segment/scripts/evaluate.py
similarity index 95%
rename from src/mednet/libs/segmentation/scripts/evaluate.py
rename to src/mednet/segment/scripts/evaluate.py
index 704f932b..36442aae 100644
--- a/src/mednet/libs/segmentation/scripts/evaluate.py
+++ b/src/mednet/segment/scripts/evaluate.py
@@ -8,8 +8,9 @@ import typing
import click
from clapper.click import ResourceOption, verbosity_option
from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
-from mednet.libs.segmentation.engine.evaluator import SUPPORTED_METRIC_TYPE
+
+from ...scripts.click import ConfigCommand
+from ..engine.evaluator import SUPPORTED_METRIC_TYPE
logger = setup("mednet")
@@ -18,7 +19,7 @@ __import__("matplotlib").use("agg")
@click.command(
- entry_point_group="mednet.libs.segmentation.config",
+ entry_point_group="mednet.config",
cls=ConfigCommand,
epilog="""Examples:
@@ -145,11 +146,12 @@ def evaluate(
"""Evaluate predictions (from a model) on a segmentation task."""
import matplotlib.backends.backend_pdf
- from mednet.libs.common.scripts.utils import (
+
+ from ...scripts.utils import (
save_json_metadata,
save_json_with_backup,
)
- from mednet.libs.segmentation.engine.evaluator import (
+ from ..engine.evaluator import (
compare_annotators,
make_plots,
make_table,
diff --git a/src/mednet/libs/segmentation/scripts/view.py b/src/mednet/segment/scripts/view.py
similarity index 92%
rename from src/mednet/libs/segmentation/scripts/view.py
rename to src/mednet/segment/scripts/view.py
index 70398b3b..41199082 100644
--- a/src/mednet/libs/segmentation/scripts/view.py
+++ b/src/mednet/segment/scripts/view.py
@@ -10,14 +10,15 @@ import click
import tqdm
from clapper.click import ResourceOption, verbosity_option
from clapper.logging import setup
-from mednet.libs.common.scripts.click import ConfigCommand
-from mednet.libs.segmentation.engine.evaluator import SUPPORTED_METRIC_TYPE
+
+from ...scripts.click import ConfigCommand
+from ..engine.evaluator import SUPPORTED_METRIC_TYPE
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
@click.command(
- entry_point_group="mednet.libs.segmentation.config",
+ entry_point_group="mednet.config",
cls=ConfigCommand,
epilog="""Examples:
@@ -133,18 +134,15 @@ def view(
"""Evaluate predictions (from a model) on a segmentation task."""
import numpy
- from mednet.libs.common.scripts.utils import (
- execution_metadata,
- save_json_with_backup,
- )
- from mednet.libs.segmentation.engine.evaluator import (
+
+ from ...scripts.utils import execution_metadata, save_json_with_backup
+ from ..engine.evaluator import (
compute_metric,
load_count,
name2metric,
+ validate_threshold,
)
- from mednet.libs.segmentation.engine.viewer import view
-
- from ..engine.evaluator import validate_threshold
+ from ..engine.viewer import view
view_filename = "view.json"
view_file = output_folder / view_filename
diff --git a/src/mednet/libs/segmentation/models/__init__.py b/src/mednet/utils/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/models/__init__.py
rename to src/mednet/utils/__init__.py
diff --git a/src/mednet/libs/common/utils/checkpointer.py b/src/mednet/utils/checkpointer.py
similarity index 100%
rename from src/mednet/libs/common/utils/checkpointer.py
rename to src/mednet/utils/checkpointer.py
diff --git a/src/mednet/libs/common/utils/rc.py b/src/mednet/utils/rc.py
similarity index 100%
rename from src/mednet/libs/common/utils/rc.py
rename to src/mednet/utils/rc.py
diff --git a/src/mednet/libs/common/utils/resources.py b/src/mednet/utils/resources.py
similarity index 99%
rename from src/mednet/libs/common/utils/resources.py
rename to src/mednet/utils/resources.py
index aaa1b6f0..5b8844a1 100644
--- a/src/mednet/libs/common/utils/resources.py
+++ b/src/mednet/utils/resources.py
@@ -17,7 +17,8 @@ import warnings
import numpy
import psutil
-from mednet.libs.common.engine.device import SupportedPytorchDevice
+
+from ..engine.device import SupportedPytorchDevice
logger = logging.getLogger(__name__)
diff --git a/src/mednet/libs/common/utils/summary.py b/src/mednet/utils/summary.py
similarity index 100%
rename from src/mednet/libs/common/utils/summary.py
rename to src/mednet/utils/summary.py
diff --git a/src/mednet/libs/common/utils/tensorboard.py b/src/mednet/utils/tensorboard.py
similarity index 100%
rename from src/mednet/libs/common/utils/tensorboard.py
rename to src/mednet/utils/tensorboard.py
diff --git a/tests/classification/__init__.py b/tests/classification/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/src/mednet/libs/segmentation/models/backbones/__init__.py b/tests/classify/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/models/backbones/__init__.py
rename to tests/classify/__init__.py
diff --git a/tests/classification/data/histograms/models/histograms_alexnet_montgomery_default.json b/tests/classify/data/histograms/models/histograms_alexnet_montgomery_default.json
similarity index 100%
rename from tests/classification/data/histograms/models/histograms_alexnet_montgomery_default.json
rename to tests/classify/data/histograms/models/histograms_alexnet_montgomery_default.json
diff --git a/tests/classification/data/histograms/models/histograms_densenet-121_montgomery_default.json b/tests/classify/data/histograms/models/histograms_densenet-121_montgomery_default.json
similarity index 100%
rename from tests/classification/data/histograms/models/histograms_densenet-121_montgomery_default.json
rename to tests/classify/data/histograms/models/histograms_densenet-121_montgomery_default.json
diff --git a/tests/classification/data/histograms/models/histograms_pasa_montgomery_default.json b/tests/classify/data/histograms/models/histograms_pasa_montgomery_default.json
similarity index 100%
rename from tests/classification/data/histograms/models/histograms_pasa_montgomery_default.json
rename to tests/classify/data/histograms/models/histograms_pasa_montgomery_default.json
diff --git a/tests/classification/data/histograms/raw_data/histograms_hivtb_fold_0.json b/tests/classify/data/histograms/raw_data/histograms_hivtb_fold_0.json
similarity index 100%
rename from tests/classification/data/histograms/raw_data/histograms_hivtb_fold_0.json
rename to tests/classify/data/histograms/raw_data/histograms_hivtb_fold_0.json
diff --git a/tests/classification/data/histograms/raw_data/histograms_indian_default.json b/tests/classify/data/histograms/raw_data/histograms_indian_default.json
similarity index 100%
rename from tests/classification/data/histograms/raw_data/histograms_indian_default.json
rename to tests/classify/data/histograms/raw_data/histograms_indian_default.json
diff --git a/tests/classification/data/histograms/raw_data/histograms_montgomery_default.json b/tests/classify/data/histograms/raw_data/histograms_montgomery_default.json
similarity index 100%
rename from tests/classification/data/histograms/raw_data/histograms_montgomery_default.json
rename to tests/classify/data/histograms/raw_data/histograms_montgomery_default.json
diff --git a/tests/classification/data/histograms/raw_data/histograms_montgomery_preprocessed_default.json b/tests/classify/data/histograms/raw_data/histograms_montgomery_preprocessed_default.json
similarity index 100%
rename from tests/classification/data/histograms/raw_data/histograms_montgomery_preprocessed_default.json
rename to tests/classify/data/histograms/raw_data/histograms_montgomery_preprocessed_default.json
diff --git a/tests/classification/data/histograms/raw_data/histograms_nih_cxr14_default.json b/tests/classify/data/histograms/raw_data/histograms_nih_cxr14_default.json
similarity index 100%
rename from tests/classification/data/histograms/raw_data/histograms_nih_cxr14_default.json
rename to tests/classify/data/histograms/raw_data/histograms_nih_cxr14_default.json
diff --git a/tests/classification/data/histograms/raw_data/histograms_padchest_idiap.json b/tests/classify/data/histograms/raw_data/histograms_padchest_idiap.json
similarity index 100%
rename from tests/classification/data/histograms/raw_data/histograms_padchest_idiap.json
rename to tests/classify/data/histograms/raw_data/histograms_padchest_idiap.json
diff --git a/tests/classification/data/histograms/raw_data/histograms_shenzhen_default.json b/tests/classify/data/histograms/raw_data/histograms_shenzhen_default.json
similarity index 100%
rename from tests/classification/data/histograms/raw_data/histograms_shenzhen_default.json
rename to tests/classify/data/histograms/raw_data/histograms_shenzhen_default.json
diff --git a/tests/classification/data/histograms/raw_data/histograms_tbpoc_fold_0.json b/tests/classify/data/histograms/raw_data/histograms_tbpoc_fold_0.json
similarity index 100%
rename from tests/classification/data/histograms/raw_data/histograms_tbpoc_fold_0.json
rename to tests/classify/data/histograms/raw_data/histograms_tbpoc_fold_0.json
diff --git a/tests/classification/data/histograms/raw_data/histograms_tbx11k_v1_fold_0.json b/tests/classify/data/histograms/raw_data/histograms_tbx11k_v1_fold_0.json
similarity index 100%
rename from tests/classification/data/histograms/raw_data/histograms_tbx11k_v1_fold_0.json
rename to tests/classify/data/histograms/raw_data/histograms_tbx11k_v1_fold_0.json
diff --git a/tests/classification/data/histograms/raw_data/histograms_tbx11k_v2_fold_0.json b/tests/classify/data/histograms/raw_data/histograms_tbx11k_v2_fold_0.json
similarity index 100%
rename from tests/classification/data/histograms/raw_data/histograms_tbx11k_v2_fold_0.json
rename to tests/classify/data/histograms/raw_data/histograms_tbx11k_v2_fold_0.json
diff --git a/tests/classification/data/test_predictions.csv b/tests/classify/data/test_predictions.csv
similarity index 100%
rename from tests/classification/data/test_predictions.csv
rename to tests/classify/data/test_predictions.csv
diff --git a/tests/classification/data/test_vis_metrics.csv b/tests/classify/data/test_vis_metrics.csv
similarity index 100%
rename from tests/classification/data/test_vis_metrics.csv
rename to tests/classify/data/test_vis_metrics.csv
diff --git a/tests/classification/test_cli.py b/tests/classify/test_cli.py
similarity index 80%
rename from tests/classification/test_cli.py
rename to tests/classify/test_cli.py
index 865b166c..d74c4385 100644
--- a/tests/classification/test_cli.py
+++ b/tests/classify/test_cli.py
@@ -40,46 +40,9 @@ def _check_help(entry_point):
assert result.output.startswith("Usage:")
-def test_config_help():
- from mednet.libs.classification.scripts.config import config
-
- _check_help(config)
-
-
-def test_config_list_help():
- from mednet.libs.classification.scripts.config import list_
-
- _check_help(list_)
-
-
-def test_config_list():
- from mednet.libs.classification.scripts.config import list_
-
- runner = CliRunner()
- result = runner.invoke(list_)
- _assert_exit_0(result)
- assert "module: mednet.libs.classification.config.data" in result.output
- assert "module: mednet.libs.classification.config.models" in result.output
-
-
-def test_config_list_v():
- from mednet.libs.classification.scripts.config import list_
-
- result = CliRunner().invoke(list_, ["--verbose"])
- _assert_exit_0(result)
- assert "module: mednet.libs.classification.config.data" in result.output
- assert "module: mednet.libs.classification.config.models" in result.output
-
-
-def test_config_describe_help():
- from mednet.libs.classification.scripts.config import describe
-
- _check_help(describe)
-
-
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_config_describe_montgomery():
- from mednet.libs.classification.scripts.config import describe
+ from mednet.scripts.config import describe
runner = CliRunner()
result = runner.invoke(describe, ["montgomery"])
@@ -87,36 +50,9 @@ def test_config_describe_montgomery():
assert "Montgomery DataModule for TB detection." in result.output
-def test_database_help():
- from mednet.libs.classification.scripts.database import database
-
- _check_help(database)
-
-
-def test_datamodule_list_help():
- from mednet.libs.classification.scripts.database import list_
-
- _check_help(list_)
-
-
-def test_datamodule_list():
- from mednet.libs.classification.scripts.database import list_
-
- runner = CliRunner()
- result = runner.invoke(list_)
- _assert_exit_0(result)
- assert result.output.startswith("Available databases:")
-
-
-def test_datamodule_check_help():
- from mednet.libs.classification.scripts.database import check
-
- _check_help(check)
-
-
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["--verbose", "--limit=1", "montgomery"])
@@ -124,41 +60,29 @@ def test_database_check():
def test_main_help():
- from mednet.libs.classification.scripts.cli import classification
-
- _check_help(classification)
-
+ from mednet.classify.scripts.cli import classify
-def test_train_help():
- from mednet.libs.classification.scripts.train import train
-
- _check_help(train)
+ _check_help(classify)
def _str_counter(substr, s):
return sum(1 for _ in re.finditer(substr, s, re.MULTILINE))
-def test_predict_help():
- from mednet.libs.classification.scripts.predict import predict
-
- _check_help(predict)
-
-
def test_evaluate_help():
- from mednet.libs.classification.scripts.evaluate import evaluate
+ from mednet.classify.scripts.evaluate import evaluate
_check_help(evaluate)
def test_saliency_generate_help():
- from mednet.libs.classification.scripts.saliency.generate import generate
+ from mednet.classify.scripts.saliency.generate import generate
_check_help(generate)
def test_saliency_completeness_help():
- from mednet.libs.classification.scripts.saliency.completeness import (
+ from mednet.classify.scripts.saliency.completeness import (
completeness,
)
@@ -166,28 +90,22 @@ def test_saliency_completeness_help():
def test_saliency_view_help():
- from mednet.libs.classification.scripts.saliency.view import view
+ from mednet.classify.scripts.saliency.view import view
_check_help(view)
def test_saliency_evaluate_help():
- from mednet.libs.classification.scripts.saliency.evaluate import evaluate
+ from mednet.classify.scripts.saliency.evaluate import evaluate
_check_help(evaluate)
-def test_upload_help():
- from mednet.libs.classification.scripts.upload import upload
-
- _check_help(upload)
-
-
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_train_pasa_montgomery(session_tmp_path):
- from mednet.libs.classification.scripts.train import train
- from mednet.libs.common.utils.checkpointer import (
+ from mednet.scripts.train import train
+ from mednet.utils.checkpointer import (
CHECKPOINT_EXTENSION,
_get_checkpoint_from_alias,
)
@@ -242,8 +160,8 @@ def test_train_pasa_montgomery(session_tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_predict_pasa_montgomery(session_tmp_path):
- from mednet.libs.classification.scripts.predict import predict
- from mednet.libs.common.utils.checkpointer import (
+ from mednet.scripts.predict import predict
+ from mednet.utils.checkpointer import (
CHECKPOINT_EXTENSION,
_get_checkpoint_from_alias,
)
@@ -295,7 +213,7 @@ def test_predict_pasa_montgomery(session_tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_evaluate_pasa_montgomery(session_tmp_path):
- from mednet.libs.classification.scripts.evaluate import evaluate
+ from mednet.classify.scripts.evaluate import evaluate
runner = CliRunner()
@@ -339,8 +257,8 @@ def test_evaluate_pasa_montgomery(session_tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_saliency_generation_pasa_montgomery(session_tmp_path):
- from mednet.libs.classification.scripts.saliency.generate import generate
- from mednet.libs.common.utils.checkpointer import (
+ from mednet.classify.scripts.saliency.generate import generate
+ from mednet.utils.checkpointer import (
CHECKPOINT_EXTENSION,
_get_checkpoint_from_alias,
)
@@ -386,8 +304,8 @@ def test_saliency_generation_pasa_montgomery(session_tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_saliency_view_pasa_montgomery(session_tmp_path):
- from mednet.libs.classification.scripts.saliency.view import view
- from mednet.libs.common.utils.checkpointer import (
+ from mednet.classify.scripts.saliency.view import view
+ from mednet.utils.checkpointer import (
CHECKPOINT_EXTENSION,
_get_checkpoint_from_alias,
)
@@ -434,8 +352,8 @@ def test_saliency_view_pasa_montgomery(session_tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_train_pasa_montgomery_from_checkpoint(tmp_path):
- from mednet.libs.classification.scripts.train import train
- from mednet.libs.common.utils.checkpointer import (
+ from mednet.scripts.train import train
+ from mednet.utils.checkpointer import (
CHECKPOINT_EXTENSION,
_get_checkpoint_from_alias,
)
@@ -511,7 +429,7 @@ def test_train_pasa_montgomery_from_checkpoint(tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_experiment(tmp_path):
- from mednet.libs.classification.scripts.experiment import experiment
+ from mednet.scripts.experiment import experiment
runner = CliRunner()
diff --git a/tests/classification/test_evaluator.py b/tests/classify/test_evaluator.py
similarity index 85%
rename from tests/classification/test_evaluator.py
rename to tests/classify/test_evaluator.py
index f3291043..b62d4c7a 100644
--- a/tests/classification/test_evaluator.py
+++ b/tests/classify/test_evaluator.py
@@ -7,7 +7,7 @@ import numpy
def test_centered_maxf1():
- from mednet.libs.classification.engine.evaluator import _get_centered_maxf1
+ from mednet.classify.engine.evaluator import _get_centered_maxf1
# Multiple max F1
f1_scores = numpy.array([0.8, 0.9, 1.0, 1.0, 1.0, 0.3])
@@ -29,8 +29,8 @@ def test_centered_maxf1():
def test_run_binary_1():
- from mednet.libs.classification.engine.evaluator import run_binary
- from mednet.libs.classification.models.typing import BinaryPrediction
+ from mednet.classify.engine.evaluator import run_binary
+ from mednet.classify.models.typing import BinaryPrediction
predictions: list[BinaryPrediction] = [
# (name, target, predicted-value)
@@ -53,7 +53,7 @@ def test_run_binary_1():
assert numpy.isclose(results["precision"], 1 / 2) # tp / (tp + fp)
assert numpy.isclose(results["recall"], 1 / 2) # tp / (tp + fn)
assert numpy.isclose(
- results["f1_score"],
+ results["f1"],
2 * (1 / 2 * 1 / 2) / (1 / 2 + 1 / 2),
) # 2 * (prec. * recall) / (prec. + recall)
assert numpy.isclose(
@@ -71,7 +71,7 @@ def test_run_binary_1():
# 0.8 | 1 | 0 | 0.5
# 0.9 | 1 | 0 | 0
# > 0.9 | 1 | 0 | 0
- assert numpy.isclose(results["auc_score"], 0.75)
+ assert numpy.isclose(results["roc_auc"], 0.75)
# threshold table:
# threshold | Prec. | Recall
@@ -82,12 +82,12 @@ def test_run_binary_1():
# 0.8 | 1 | 0.5
# 0.9 | 0 | 0
# > 0.9 | 0 | 0
- assert numpy.isclose(results["average_precision_score"], 0.8333333)
+ assert numpy.isclose(results["average_precision"], 0.8333333)
def test_run_binary_2():
- from mednet.libs.classification.engine.evaluator import run_binary
- from mednet.libs.classification.models.typing import BinaryPrediction
+ from mednet.classify.engine.evaluator import run_binary
+ from mednet.classify.models.typing import BinaryPrediction
predictions: list[BinaryPrediction] = [
# (name, target, predicted-value)
@@ -112,7 +112,7 @@ def test_run_binary_2():
assert numpy.isclose(results["precision"], 2 / 3) # tp / (tp + fp)
assert numpy.isclose(results["recall"], 2 / 2) # tp / (tp + fn)
assert numpy.isclose(
- results["f1_score"],
+ results["f1"],
2 * (2 / 3 * 2 / 2) / (2 / 3 + 2 / 2),
) # 2 * (prec. * recall) / (prec. + recall)
assert numpy.isclose(
@@ -130,7 +130,7 @@ def test_run_binary_2():
# 0.8 | 1 | 0 | 0.5
# 0.9 | 1 | 0 | 0
# > 0.9 | 1 | 0 | 0
- assert numpy.isclose(results["auc_score"], 0.75)
+ assert numpy.isclose(results["roc_auc"], 0.75)
# threshold table:
# threshold | Prec. | Recall
@@ -141,4 +141,4 @@ def test_run_binary_2():
# 0.8 | 1 | 0.5
# 0.9 | 0 | 0
# > 0.9 | 0 | 0
- assert numpy.isclose(results["average_precision_score"], 0.8333333)
+ assert numpy.isclose(results["average_precision"], 0.8333333)
diff --git a/tests/classification/test_hivtb.py b/tests/classify/test_hivtb.py
similarity index 90%
rename from tests/classification/test_hivtb.py
rename to tests/classify/test_hivtb.py
index 547346fd..83b76d8b 100644
--- a/tests/classification/test_hivtb.py
+++ b/tests/classify/test_hivtb.py
@@ -36,10 +36,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.classification.config.data.hivtb", f"{split}.json"),
+ make_split("mednet.classify.config.data.hivtb", f"{split}.json"),
lengths=lengths,
prefixes=("HIV-TB_Algorithm_study_X-rays",),
possible_labels=(0, 1),
@@ -48,7 +48,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.hivtb")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["--limit=10", "hivtb-f0"])
@@ -84,7 +84,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.hivtb",
+ "mednet.classify.config.data.hivtb",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -116,7 +116,7 @@ def test_loaded_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".fold_0",
- "mednet.libs.classification.config.data.hivtb",
+ "mednet.classify.config.data.hivtb",
).datamodule
datamodule.model_transforms = []
diff --git a/tests/classification/test_indian.py b/tests/classify/test_indian.py
similarity index 91%
rename from tests/classification/test_indian.py
rename to tests/classify/test_indian.py
index dcd4236f..0a3262b9 100644
--- a/tests/classification/test_indian.py
+++ b/tests/classify/test_indian.py
@@ -40,10 +40,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.classification.config.data.indian", f"{split}.json"),
+ make_split("mednet.classify.config.data.indian", f"{split}.json"),
lengths=lengths,
prefixes=("DatasetA/Training", "DatasetA/Testing"),
possible_labels=(0, 1),
@@ -52,7 +52,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.indian")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["indian"])
@@ -89,7 +89,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.indian",
+ "mednet.classify.config.data.indian",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -121,7 +121,7 @@ def test_loaded_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".default",
- "mednet.libs.classification.config.data.indian",
+ "mednet.classify.config.data.indian",
).datamodule
datamodule.model_transforms = []
diff --git a/tests/classification/test_montgomery.py b/tests/classify/test_montgomery.py
similarity index 91%
rename from tests/classification/test_montgomery.py
rename to tests/classify/test_montgomery.py
index 494528dc..464f92f4 100644
--- a/tests/classification/test_montgomery.py
+++ b/tests/classify/test_montgomery.py
@@ -38,12 +38,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split(
- "mednet.libs.classification.config.data.montgomery", f"{split}.json"
- ),
+ make_split("mednet.classify.config.data.montgomery", f"{split}.json"),
lengths=lengths,
prefixes=("CXR_png/MCUCXR_0",),
possible_labels=(0, 1),
@@ -52,7 +50,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["montgomery"])
@@ -89,7 +87,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -118,7 +116,7 @@ def test_loading(database_checkers, name: str, dataset: str):
def test_raw_transforms_image_quality(database_checkers, datadir: pathlib.Path):
datamodule = importlib.import_module(
".default",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).datamodule
datamodule.model_transforms = []
@@ -154,12 +152,12 @@ def test_model_transforms_image_quality(
):
datamodule = importlib.import_module(
".default",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).datamodule
model = importlib.import_module(
f".{model_name}",
- "mednet.libs.classification.config.models",
+ "mednet.classify.config.models",
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/classification/test_montgomery_shenzhen.py b/tests/classify/test_montgomery_shenzhen.py
similarity index 83%
rename from tests/classification/test_montgomery_shenzhen.py
rename to tests/classify/test_montgomery_shenzhen.py
index 57cac2cf..b94797c0 100644
--- a/tests/classification/test_montgomery_shenzhen.py
+++ b/tests/classify/test_montgomery_shenzhen.py
@@ -28,27 +28,27 @@ from click.testing import CliRunner
def test_split_consistency(name: str):
montgomery = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).datamodule
shenzhen = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.shenzhen",
+ "mednet.classify.config.data.shenzhen",
).datamodule
combined = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.montgomery_shenzhen",
+ "mednet.classify.config.data.montgomery_shenzhen",
).datamodule
montgomery_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).ClassificationRawDataLoader
shenzhen_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.shenzhen",
+ "mednet.classify.config.data.shenzhen",
).ClassificationRawDataLoader
for split in ("train", "validation", "test"):
@@ -65,7 +65,7 @@ def test_split_consistency(name: str):
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
@pytest.mark.skip_if_rc_var_not_set("datadir.shenzhen")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["montgomery-shenzhen"])
diff --git a/tests/classification/test_montgomery_shenzhen_indian.py b/tests/classify/test_montgomery_shenzhen_indian.py
similarity index 82%
rename from tests/classification/test_montgomery_shenzhen_indian.py
rename to tests/classify/test_montgomery_shenzhen_indian.py
index b1f0ec09..75fd6177 100644
--- a/tests/classification/test_montgomery_shenzhen_indian.py
+++ b/tests/classify/test_montgomery_shenzhen_indian.py
@@ -28,37 +28,37 @@ from click.testing import CliRunner
def test_split_consistency(name: str):
montgomery = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).datamodule
shenzhen = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.shenzhen",
+ "mednet.classify.config.data.shenzhen",
).datamodule
indian = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.indian",
+ "mednet.classify.config.data.indian",
).datamodule
combined = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.montgomery_shenzhen_indian",
+ "mednet.classify.config.data.montgomery_shenzhen_indian",
).datamodule
montgomery_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).ClassificationRawDataLoader
shenzhen_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.shenzhen",
+ "mednet.classify.config.data.shenzhen",
).ClassificationRawDataLoader
indian_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.indian",
+ "mednet.classify.config.data.indian",
).ClassificationRawDataLoader
for split in ("train", "validation", "test"):
@@ -80,7 +80,7 @@ def test_split_consistency(name: str):
@pytest.mark.skip_if_rc_var_not_set("datadir.indian")
@pytest.mark.skip_if_rc_var_not_set("datadir.shenzhen")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["montgomery-shenzhen-indian"])
diff --git a/tests/classification/test_montgomery_shenzhen_indian_padchest.py b/tests/classify/test_montgomery_shenzhen_indian_padchest.py
similarity index 81%
rename from tests/classification/test_montgomery_shenzhen_indian_padchest.py
rename to tests/classify/test_montgomery_shenzhen_indian_padchest.py
index 3872fb1b..647625b6 100644
--- a/tests/classification/test_montgomery_shenzhen_indian_padchest.py
+++ b/tests/classify/test_montgomery_shenzhen_indian_padchest.py
@@ -18,47 +18,47 @@ from click.testing import CliRunner
def test_split_consistency(name: str, padchest_name: str):
montgomery = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).datamodule
shenzhen = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.shenzhen",
+ "mednet.classify.config.data.shenzhen",
).datamodule
indian = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.indian",
+ "mednet.classify.config.data.indian",
).datamodule
padchest = importlib.import_module(
f".{padchest_name}",
- "mednet.libs.classification.config.data.padchest",
+ "mednet.classify.config.data.padchest",
).datamodule
combined = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.montgomery_shenzhen_indian_padchest",
+ "mednet.classify.config.data.montgomery_shenzhen_indian_padchest",
).datamodule
montgomery_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).ClassificationRawDataLoader
shenzhen_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.shenzhen",
+ "mednet.classify.config.data.shenzhen",
).ClassificationRawDataLoader
indian_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.indian",
+ "mednet.classify.config.data.indian",
).ClassificationRawDataLoader
padchest_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.padchest",
+ "mednet.classify.config.data.padchest",
).ClassificationRawDataLoader
for split in ("train", "validation", "test"):
@@ -87,7 +87,7 @@ def test_split_consistency(name: str, padchest_name: str):
@pytest.mark.skip_if_rc_var_not_set("datadir.indian")
@pytest.mark.skip_if_rc_var_not_set("datadir.padchest")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["montgomery-shenzhen-indian-padchest"])
diff --git a/tests/classification/test_montgomery_shenzhen_indian_tbx11k.py b/tests/classify/test_montgomery_shenzhen_indian_tbx11k.py
similarity index 85%
rename from tests/classification/test_montgomery_shenzhen_indian_tbx11k.py
rename to tests/classify/test_montgomery_shenzhen_indian_tbx11k.py
index 5500d3e0..44a2f18f 100644
--- a/tests/classification/test_montgomery_shenzhen_indian_tbx11k.py
+++ b/tests/classify/test_montgomery_shenzhen_indian_tbx11k.py
@@ -39,47 +39,47 @@ from click.testing import CliRunner
def test_split_consistency(name: str, tbx11k_name: str):
montgomery = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).datamodule
shenzhen = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.shenzhen",
+ "mednet.classify.config.data.shenzhen",
).datamodule
indian = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.indian",
+ "mednet.classify.config.data.indian",
).datamodule
tbx11k = importlib.import_module(
f".{tbx11k_name}",
- "mednet.libs.classification.config.data.tbx11k",
+ "mednet.classify.config.data.tbx11k",
).datamodule
combined = importlib.import_module(
f".{tbx11k_name}",
- "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k",
+ "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k",
).datamodule
montgomery_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.montgomery",
+ "mednet.classify.config.data.montgomery",
).ClassificationRawDataLoader
shenzhen_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.shenzhen",
+ "mednet.classify.config.data.shenzhen",
).ClassificationRawDataLoader
indian_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.indian",
+ "mednet.classify.config.data.indian",
).ClassificationRawDataLoader
tbx11k_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.tbx11k",
+ "mednet.classify.config.data.tbx11k",
).ClassificationRawDataLoader
for split in ("train", "validation", "test"):
@@ -115,7 +115,7 @@ def test_split_consistency(name: str, tbx11k_name: str):
def test_batch_uniformity(tbx11k_name: str, dataset: str):
combined = importlib.import_module(
f".{tbx11k_name}",
- "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k",
+ "mednet.classify.config.data.montgomery_shenzhen_indian_tbx11k",
).datamodule
combined.model_transforms = [] # should be done before setup()
@@ -136,7 +136,7 @@ def test_batch_uniformity(tbx11k_name: str, dataset: str):
@pytest.mark.skip_if_rc_var_not_set("datadir.indian")
@pytest.mark.skip_if_rc_var_not_set("datadir.tbx11k")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["montgomery-shenzhen-indian-tbx11k-v1"])
diff --git a/tests/classification/test_nih_cxr14.py b/tests/classify/test_nih_cxr14.py
similarity index 89%
rename from tests/classification/test_nih_cxr14.py
rename to tests/classify/test_nih_cxr14.py
index 1d2c2222..2612554e 100644
--- a/tests/classification/test_nih_cxr14.py
+++ b/tests/classify/test_nih_cxr14.py
@@ -28,10 +28,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.classification.config.data.nih_cxr14", f"{split}"),
+ make_split("mednet.classify.config.data.nih_cxr14", f"{split}"),
lengths=lengths,
prefixes=("images/000",),
possible_labels=(0, 1),
@@ -49,7 +49,7 @@ testdata = [
@pytest.mark.skip_if_rc_var_not_set("datadir.nih_cxr14")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["--limit=10", "nih-cxr14"])
@@ -63,7 +63,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str, num_labels: int):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.nih_cxr14",
+ "mednet.classify.config.data.nih_cxr14",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -96,7 +96,7 @@ def test_loaded_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".default",
- "mednet.libs.classification.config.data.nih_cxr14",
+ "mednet.classify.config.data.nih_cxr14",
).datamodule
datamodule.model_transforms = []
diff --git a/tests/classification/test_nih_cxr14_padchest.py b/tests/classify/test_nih_cxr14_padchest.py
similarity index 83%
rename from tests/classification/test_nih_cxr14_padchest.py
rename to tests/classify/test_nih_cxr14_padchest.py
index 987c2ba7..548e4240 100644
--- a/tests/classification/test_nih_cxr14_padchest.py
+++ b/tests/classify/test_nih_cxr14_padchest.py
@@ -18,27 +18,27 @@ from click.testing import CliRunner
def test_split_consistency(name: str, padchest_name: str, combined_name: str):
nih_cxr14 = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.nih_cxr14",
+ "mednet.classify.config.data.nih_cxr14",
).datamodule
padchest = importlib.import_module(
f".{padchest_name}",
- "mednet.libs.classification.config.data.padchest",
+ "mednet.classify.config.data.padchest",
).datamodule
combined = importlib.import_module(
f".{combined_name}",
- "mednet.libs.classification.config.data.nih_cxr14_padchest",
+ "mednet.classify.config.data.nih_cxr14_padchest",
).datamodule
cxr14_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.nih_cxr14",
+ "mednet.classify.config.data.nih_cxr14",
).ClassificationRawDataLoader
padchest_loader = importlib.import_module(
".datamodule",
- "mednet.libs.classification.config.data.padchest",
+ "mednet.classify.config.data.padchest",
).ClassificationRawDataLoader
for split in ("train", "validation", "test"):
@@ -56,7 +56,7 @@ def test_split_consistency(name: str, padchest_name: str, combined_name: str):
@pytest.mark.skip_if_rc_var_not_set("datadir.nih_cxr14")
@pytest.mark.skip_if_rc_var_not_set("datadir.padchest")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["--limit=10", "nih-cxr14-padchest"])
diff --git a/tests/classification/test_padchest.py b/tests/classify/test_padchest.py
similarity index 90%
rename from tests/classification/test_padchest.py
rename to tests/classify/test_padchest.py
index 78ce812a..e5fc35a6 100644
--- a/tests/classification/test_padchest.py
+++ b/tests/classify/test_padchest.py
@@ -33,10 +33,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.classification.config.data.padchest", split),
+ make_split("mednet.classify.config.data.padchest", split),
lengths=lengths,
prefixes=("",),
possible_labels=(0, 1),
@@ -45,7 +45,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.padchest")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["--limit=10", "padchest-idiap"])
@@ -68,7 +68,7 @@ testdata = [
def test_loading(database_checkers, name: str, dataset: str, num_labels: int):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.padchest",
+ "mednet.classify.config.data.padchest",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -101,7 +101,7 @@ def test_loaded_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".idiap",
- "mednet.libs.classification.config.data.padchest",
+ "mednet.classify.config.data.padchest",
).datamodule
datamodule.model_transforms = []
diff --git a/tests/classification/test_saliencymap_interpretability.py b/tests/classify/test_saliencymap_interpretability.py
similarity index 97%
rename from tests/classification/test_saliencymap_interpretability.py
rename to tests/classify/test_saliencymap_interpretability.py
index c91115d4..5a5d1fb7 100644
--- a/tests/classification/test_saliencymap_interpretability.py
+++ b/tests/classify/test_saliencymap_interpretability.py
@@ -2,11 +2,11 @@
#
# SPDX-License-Identifier: GPL-3.0-or-later
import numpy as np
-from mednet.libs.classification.config.data.tbx11k.datamodule import (
+from mednet.classify.config.data.tbx11k.datamodule import (
BoundingBox,
BoundingBoxes,
)
-from mednet.libs.classification.engine.saliency.interpretability import (
+from mednet.classify.engine.saliency.interpretability import (
_compute_avg_saliency_focus,
_compute_binary_mask,
_compute_max_iou_and_ioda,
diff --git a/tests/classification/test_shenzhen.py b/tests/classify/test_shenzhen.py
similarity index 90%
rename from tests/classification/test_shenzhen.py
rename to tests/classify/test_shenzhen.py
index 2c31ac26..4df77f3c 100644
--- a/tests/classification/test_shenzhen.py
+++ b/tests/classify/test_shenzhen.py
@@ -37,10 +37,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.classification.config.data.shenzhen", f"{split}.json"),
+ make_split("mednet.classify.config.data.shenzhen", f"{split}.json"),
lengths=lengths,
prefixes=("CXR_png/CHNCXR_0",),
possible_labels=(0, 1),
@@ -49,7 +49,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.shenzhen")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["shenzhen"])
@@ -86,7 +86,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.shenzhen",
+ "mednet.classify.config.data.shenzhen",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -118,7 +118,7 @@ def test_loaded_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".default",
- "mednet.libs.classification.config.data.shenzhen",
+ "mednet.classify.config.data.shenzhen",
).datamodule
datamodule.model_transforms = []
diff --git a/tests/classification/test_summary.py b/tests/classify/test_summary.py
similarity index 77%
rename from tests/classification/test_summary.py
rename to tests/classify/test_summary.py
index c9d86ffc..b214800a 100644
--- a/tests/classification/test_summary.py
+++ b/tests/classify/test_summary.py
@@ -4,8 +4,8 @@
import unittest
-import mednet.libs.classification.config.models.pasa as pasa_config
-from mednet.libs.common.utils.summary import summary
+import mednet.classify.config.models.pasa as pasa_config
+from mednet.utils.summary import summary
class Tester(unittest.TestCase):
diff --git a/tests/classification/test_tbpoc.py b/tests/classify/test_tbpoc.py
similarity index 87%
rename from tests/classification/test_tbpoc.py
rename to tests/classify/test_tbpoc.py
index 66dcd46a..ac809be3 100644
--- a/tests/classification/test_tbpoc.py
+++ b/tests/classify/test_tbpoc.py
@@ -36,10 +36,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.classification.config.data.tbpoc", f"{split}.json"),
+ make_split("mednet.classify.config.data.tbpoc", f"{split}.json"),
lengths=lengths,
prefixes=(
"TBPOC_CXR/TBPOC-",
@@ -51,7 +51,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.tbpoc")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["tbpoc-f0"])
@@ -87,7 +87,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.tbpoc",
+ "mednet.classify.config.data.tbpoc",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -103,10 +103,7 @@ def test_loading(database_checkers, name: str, dataset: str):
batch,
batch_size=1,
color_planes=1,
- prefixes=(
- "TBPOC_CXR/TBPOC-",
- "TBPOC_CXR/tbpoc-",
- ),
+ prefixes=("TBPOC_CXR/TBPOC-", "TBPOC_CXR/tbpoc-"),
possible_labels=(0, 1),
expected_num_labels=1,
expected_meta_size=2,
@@ -121,8 +118,7 @@ def test_loaded_image_quality(database_checkers, datadir):
)
datamodule = importlib.import_module(
- ".fold_0",
- "mednet.libs.classification.config.data.tbpoc",
+ ".fold_0", "mednet.classify.config.data.tbpoc"
).datamodule
datamodule.model_transforms = []
diff --git a/tests/classification/test_tbx11k.py b/tests/classify/test_tbx11k.py
similarity index 96%
rename from tests/classification/test_tbx11k.py
rename to tests/classify/test_tbx11k.py
index 932b8782..7a5a5625 100644
--- a/tests/classification/test_tbx11k.py
+++ b/tests/classify/test_tbx11k.py
@@ -139,10 +139,10 @@ def test_protocol_consistency(
lengths: dict[str, int],
prefixes: typing.Sequence[str],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.classification.config.data.tbx11k", f"{split}.json"),
+ make_split("mednet.classify.config.data.tbx11k", f"{split}.json"),
lengths=lengths,
prefixes=prefixes,
possible_labels=(0, 1),
@@ -234,7 +234,7 @@ def check_loaded_batch(
@pytest.mark.skip_if_rc_var_not_set("datadir.tbx11k")
def test_database_check():
- from mednet.libs.classification.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["--limit=10", "tbx11k-v1-f0"])
@@ -287,7 +287,7 @@ def test_database_check():
def test_loading(name: str, dataset: str, prefixes: typing.Sequence[str]):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.classification.config.data.tbx11k",
+ "mednet.classify.config.data.tbx11k",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -326,7 +326,7 @@ def test_loaded_image_quality(database_checkers, datadir, split):
datamodule = importlib.import_module(
f".{split}",
- "mednet.libs.classification.config.data.tbx11k",
+ "mednet.classify.config.data.tbx11k",
).datamodule
datamodule.model_transforms = []
diff --git a/tests/classification/test_visceral.py b/tests/classify/test_visceral.py
similarity index 83%
rename from tests/classification/test_visceral.py
rename to tests/classify/test_visceral.py
index 58ecd6bd..1abf23b8 100644
--- a/tests/classification/test_visceral.py
+++ b/tests/classify/test_visceral.py
@@ -25,10 +25,10 @@ def test_protocol_consistency(
split: str,
lenghts: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.classification.config.data.visceral", f"{split}.json"),
+ make_split("mednet.classify.config.data.visceral", f"{split}.json"),
lengths=lenghts,
prefixes=("16/10000"),
possible_labels=(0, 1),
@@ -37,7 +37,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.visceral")
def test_database_check():
- from mednet.libs.common.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["visceral"])
diff --git a/tests/conftest.py b/tests/conftest.py
index fad88f46..acbc89f7 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -8,8 +8,8 @@ import typing
import numpy
import pytest
import torch
-from mednet.libs.common.data.split import JSONDatabaseSplit
-from mednet.libs.common.data.typing import DatabaseSplit
+from mednet.data.split import JSONDatabaseSplit
+from mednet.data.typing import DatabaseSplit
@pytest.fixture
@@ -63,7 +63,7 @@ def pytest_runtest_setup(item):
information.
"""
- from mednet.libs.common.utils.rc import load_rc
+ from mednet.utils.rc import load_rc
rc = load_rc()
@@ -73,19 +73,19 @@ def pytest_runtest_setup(item):
mark.args[0] for mark in item.iter_markers(name="skip_if_rc_var_not_set")
]
- # checks all names mentioned are set in ~/.config/mednet.libs.classification.toml, otherwise,
+ # checks all names mentioned are set in ~/.config/mednet.toml, otherwise,
# skip the test
if rc_names:
missing = [k for k in rc_names if rc.get(k) is None]
if any(missing):
pytest.skip(
f"Test skipped because {', '.join(missing)} is **not** "
- f"set in ~/.config/mednet.libs.classification.toml",
+ f"set in ~/.config/mednet.toml",
)
def rc_variable_set(name):
- from mednet.libs.common.utils.rc import load_rc
+ from mednet.utils.rc import load_rc
rc = load_rc()
pytest.mark.skipif(
diff --git a/src/mednet/libs/segmentation/scripts/__init__.py b/tests/segment/__init__.py
similarity index 100%
rename from src/mednet/libs/segmentation/scripts/__init__.py
rename to tests/segment/__init__.py
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json b/tests/segment/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json
rename to tests/segment/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_cxr8_default.json b/tests/segment/data/histograms/models/histograms_lwnet_cxr8_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_cxr8_default.json
rename to tests/segment/data/histograms/models/histograms_lwnet_cxr8_default.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_drhagis_default.json b/tests/segment/data/histograms/models/histograms_lwnet_drhagis_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_drhagis_default.json
rename to tests/segment/data/histograms/models/histograms_lwnet_drhagis_default.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_drionsdb_expert1.json b/tests/segment/data/histograms/models/histograms_lwnet_drionsdb_expert1.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_drionsdb_expert1.json
rename to tests/segment/data/histograms/models/histograms_lwnet_drionsdb_expert1.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_drishtigs1_optic_cup_all.json b/tests/segment/data/histograms/models/histograms_lwnet_drishtigs1_optic_cup_all.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_drishtigs1_optic_cup_all.json
rename to tests/segment/data/histograms/models/histograms_lwnet_drishtigs1_optic_cup_all.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_drive_default.json b/tests/segment/data/histograms/models/histograms_lwnet_drive_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_drive_default.json
rename to tests/segment/data/histograms/models/histograms_lwnet_drive_default.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_hrf_default.json b/tests/segment/data/histograms/models/histograms_lwnet_hrf_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_hrf_default.json
rename to tests/segment/data/histograms/models/histograms_lwnet_hrf_default.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_iostar_vessel.json b/tests/segment/data/histograms/models/histograms_lwnet_iostar_vessel.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_iostar_vessel.json
rename to tests/segment/data/histograms/models/histograms_lwnet_iostar_vessel.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_jsrt_default.json b/tests/segment/data/histograms/models/histograms_lwnet_jsrt_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_jsrt_default.json
rename to tests/segment/data/histograms/models/histograms_lwnet_jsrt_default.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_montgomery_default.json b/tests/segment/data/histograms/models/histograms_lwnet_montgomery_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_montgomery_default.json
rename to tests/segment/data/histograms/models/histograms_lwnet_montgomery_default.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_refuge_cup.json b/tests/segment/data/histograms/models/histograms_lwnet_refuge_cup.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_refuge_cup.json
rename to tests/segment/data/histograms/models/histograms_lwnet_refuge_cup.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_rimoner3_cup_exp1.json b/tests/segment/data/histograms/models/histograms_lwnet_rimoner3_cup_exp1.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_rimoner3_cup_exp1.json
rename to tests/segment/data/histograms/models/histograms_lwnet_rimoner3_cup_exp1.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_shenzhen_default.json b/tests/segment/data/histograms/models/histograms_lwnet_shenzhen_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_shenzhen_default.json
rename to tests/segment/data/histograms/models/histograms_lwnet_shenzhen_default.json
diff --git a/tests/segmentation/data/histograms/models/histograms_lwnet_stare_ah.json b/tests/segment/data/histograms/models/histograms_lwnet_stare_ah.json
similarity index 100%
rename from tests/segmentation/data/histograms/models/histograms_lwnet_stare_ah.json
rename to tests/segment/data/histograms/models/histograms_lwnet_stare_ah.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_chasedb1_first_annotator.json b/tests/segment/data/histograms/raw_data/histograms_chasedb1_first_annotator.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_chasedb1_first_annotator.json
rename to tests/segment/data/histograms/raw_data/histograms_chasedb1_first_annotator.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_cxr8_default.json b/tests/segment/data/histograms/raw_data/histograms_cxr8_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_cxr8_default.json
rename to tests/segment/data/histograms/raw_data/histograms_cxr8_default.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_drhagis_default.json b/tests/segment/data/histograms/raw_data/histograms_drhagis_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_drhagis_default.json
rename to tests/segment/data/histograms/raw_data/histograms_drhagis_default.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_drionsdb_expert1.json b/tests/segment/data/histograms/raw_data/histograms_drionsdb_expert1.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_drionsdb_expert1.json
rename to tests/segment/data/histograms/raw_data/histograms_drionsdb_expert1.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_drishtigs1_optic_cup_all.json b/tests/segment/data/histograms/raw_data/histograms_drishtigs1_optic_cup_all.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_drishtigs1_optic_cup_all.json
rename to tests/segment/data/histograms/raw_data/histograms_drishtigs1_optic_cup_all.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_drive_default.json b/tests/segment/data/histograms/raw_data/histograms_drive_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_drive_default.json
rename to tests/segment/data/histograms/raw_data/histograms_drive_default.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_hrf_default.json b/tests/segment/data/histograms/raw_data/histograms_hrf_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_hrf_default.json
rename to tests/segment/data/histograms/raw_data/histograms_hrf_default.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_iostar_vessel.json b/tests/segment/data/histograms/raw_data/histograms_iostar_vessel.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_iostar_vessel.json
rename to tests/segment/data/histograms/raw_data/histograms_iostar_vessel.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_jsrt_default.json b/tests/segment/data/histograms/raw_data/histograms_jsrt_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_jsrt_default.json
rename to tests/segment/data/histograms/raw_data/histograms_jsrt_default.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_montgomery_default.json b/tests/segment/data/histograms/raw_data/histograms_montgomery_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_montgomery_default.json
rename to tests/segment/data/histograms/raw_data/histograms_montgomery_default.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_refuge_cup.json b/tests/segment/data/histograms/raw_data/histograms_refuge_cup.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_refuge_cup.json
rename to tests/segment/data/histograms/raw_data/histograms_refuge_cup.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_rimoner3_cup_exp1.json b/tests/segment/data/histograms/raw_data/histograms_rimoner3_cup_exp1.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_rimoner3_cup_exp1.json
rename to tests/segment/data/histograms/raw_data/histograms_rimoner3_cup_exp1.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_shenzhen_default.json b/tests/segment/data/histograms/raw_data/histograms_shenzhen_default.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_shenzhen_default.json
rename to tests/segment/data/histograms/raw_data/histograms_shenzhen_default.json
diff --git a/tests/segmentation/data/histograms/raw_data/histograms_stare_ah.json b/tests/segment/data/histograms/raw_data/histograms_stare_ah.json
similarity index 100%
rename from tests/segmentation/data/histograms/raw_data/histograms_stare_ah.json
rename to tests/segment/data/histograms/raw_data/histograms_stare_ah.json
diff --git a/tests/segmentation/test_chasedb1.py b/tests/segment/test_chasedb1.py
similarity index 78%
rename from tests/segmentation/test_chasedb1.py
rename to tests/segment/test_chasedb1.py
index c9bdd898..3607d407 100644
--- a/tests/segmentation/test_chasedb1.py
+++ b/tests/segment/test_chasedb1.py
@@ -28,10 +28,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.chasedb1", f"{split}.json"),
+ make_split("mednet.segment.config.data.chasedb1", f"{split}.json"),
lengths=lengths,
prefixes=["Image_"],
possible_labels=[],
@@ -40,7 +40,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.chasedb1")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["chasedb1"])
@@ -50,24 +50,11 @@ def test_database_check():
@pytest.mark.skip_if_rc_var_not_set("datadir.chasedb1")
-@pytest.mark.parametrize(
- "dataset",
- [
- "train",
- "test",
- ],
-)
-@pytest.mark.parametrize(
- "name",
- [
- "first_annotator",
- "second_annotator",
- ],
-)
+@pytest.mark.parametrize("dataset", ["train", "test"])
+@pytest.mark.parametrize("name", ["first_annotator", "second_annotator"])
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
- f".{name}",
- "mednet.libs.segmentation.config.data.chasedb1",
+ f".{name}", "mednet.segment.config.data.chasedb1"
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -98,8 +85,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
)
datamodule = importlib.import_module(
- ".first_annotator",
- "mednet.libs.segmentation.config.data.chasedb1",
+ ".first_annotator", "mednet.segment.config.data.chasedb1"
).datamodule
datamodule.model_transforms = []
@@ -109,10 +95,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
@pytest.mark.skip_if_rc_var_not_set("datadir.chasedb1")
-@pytest.mark.parametrize(
- "model_name",
- ["lwnet"],
-)
+@pytest.mark.parametrize("model_name", ["lwnet"])
def test_model_transforms_image_quality(database_checkers, datadir, model_name):
reference_histogram_file = str(
datadir
@@ -120,13 +103,11 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
)
datamodule = importlib.import_module(
- ".first_annotator",
- "mednet.libs.segmentation.config.data.chasedb1",
+ ".first_annotator", "mednet.segment.config.data.chasedb1"
).datamodule
model = importlib.import_module(
- f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ f".{model_name}", "mednet.segment.config.models"
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_cli.py b/tests/segment/test_cli.py
similarity index 82%
rename from tests/segmentation/test_cli.py
rename to tests/segment/test_cli.py
index 75838d12..f171587f 100644
--- a/tests/segmentation/test_cli.py
+++ b/tests/segment/test_cli.py
@@ -40,46 +40,9 @@ def _check_help(entry_point):
assert result.output.startswith("Usage:")
-def test_config_help():
- from mednet.libs.segmentation.scripts.config import config
-
- _check_help(config)
-
-
-def test_config_list_help():
- from mednet.libs.segmentation.scripts.config import list_
-
- _check_help(list_)
-
-
-def test_config_list():
- from mednet.libs.segmentation.scripts.config import list_
-
- runner = CliRunner()
- result = runner.invoke(list_)
- _assert_exit_0(result)
- assert "module: mednet.libs.segmentation.config.data" in result.output
- assert "module: mednet.libs.segmentation.config.models" in result.output
-
-
-def test_config_list_v():
- from mednet.libs.segmentation.scripts.config import list_
-
- result = CliRunner().invoke(list_, ["--verbose"])
- _assert_exit_0(result)
- assert "module: mednet.libs.segmentation.config.data" in result.output
- assert "module: mednet.libs.segmentation.config.models" in result.output
-
-
-def test_config_describe_help():
- from mednet.libs.segmentation.scripts.config import describe
-
- _check_help(describe)
-
-
@pytest.mark.skip_if_rc_var_not_set("datadir.drive")
def test_config_describe_drive():
- from mednet.libs.segmentation.scripts.config import describe
+ from mednet.scripts.config import describe
runner = CliRunner()
result = runner.invoke(describe, ["drive"])
@@ -87,36 +50,9 @@ def test_config_describe_drive():
assert "DRIVE dataset for Vessel Segmentation (default protocol)." in result.output
-def test_database_help():
- from mednet.libs.segmentation.scripts.database import database
-
- _check_help(database)
-
-
-def test_datamodule_list_help():
- from mednet.libs.segmentation.scripts.database import list_
-
- _check_help(list_)
-
-
-def test_datamodule_list():
- from mednet.libs.segmentation.scripts.database import list_
-
- runner = CliRunner()
- result = runner.invoke(list_)
- _assert_exit_0(result)
- assert result.output.startswith("Available databases:")
-
-
-def test_datamodule_check_help():
- from mednet.libs.segmentation.scripts.database import check
-
- _check_help(check)
-
-
@pytest.mark.skip_if_rc_var_not_set("datadir.drive")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["--verbose", "--limit=1", "drive"])
@@ -124,41 +60,41 @@ def test_database_check():
def test_main_help():
- from mednet.libs.segmentation.scripts.cli import segmentation
+ from mednet.segment.scripts.cli import segment
- _check_help(segmentation)
+ _check_help(segment)
-def test_train_help():
- from mednet.libs.segmentation.scripts.train import train
+def _str_counter(substr, s):
+ return sum(1 for _ in re.finditer(substr, s, re.MULTILINE))
- _check_help(train)
+def test_evaluate_help():
+ from mednet.segment.scripts.evaluate import evaluate
-def _str_counter(substr, s):
- return sum(1 for _ in re.finditer(substr, s, re.MULTILINE))
+ _check_help(evaluate)
-def test_predict_help():
- from mednet.libs.segmentation.scripts.predict import predict
+def test_dump_annotations_help():
+ from mednet.segment.scripts.dump_annotations import dump_annotations
- _check_help(predict)
+ _check_help(dump_annotations)
-def test_evaluate_help():
- from mednet.libs.segmentation.scripts.evaluate import evaluate
+def test_view_help():
+ from mednet.segment.scripts.view import view
- _check_help(evaluate)
+ _check_help(view)
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.drive")
def test_train_lwnet_drive(session_tmp_path):
- from mednet.libs.common.utils.checkpointer import (
+ from mednet.scripts.train import train
+ from mednet.utils.checkpointer import (
CHECKPOINT_EXTENSION,
_get_checkpoint_from_alias,
)
- from mednet.libs.segmentation.scripts.train import train
runner = CliRunner()
@@ -207,11 +143,11 @@ def test_train_lwnet_drive(session_tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.drive")
def test_predict_lwnet_drive(session_tmp_path):
- from mednet.libs.common.utils.checkpointer import (
+ from mednet.scripts.predict import predict
+ from mednet.utils.checkpointer import (
CHECKPOINT_EXTENSION,
_get_checkpoint_from_alias,
)
- from mednet.libs.segmentation.scripts.predict import predict
runner = CliRunner()
@@ -259,7 +195,7 @@ def test_predict_lwnet_drive(session_tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.drive")
def test_dump_annotations_lwnet_drive(session_tmp_path):
- from mednet.libs.segmentation.scripts.dump_annotations import dump_annotations
+ from mednet.segment.scripts.dump_annotations import dump_annotations
runner = CliRunner()
@@ -301,7 +237,7 @@ def test_dump_annotations_lwnet_drive(session_tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.drive")
def test_evaluate_lwnet_drive(session_tmp_path):
- from mednet.libs.segmentation.scripts.evaluate import evaluate
+ from mednet.segment.scripts.evaluate import evaluate
runner = CliRunner()
@@ -348,7 +284,7 @@ def test_evaluate_lwnet_drive(session_tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.drive")
def test_view_lwnet_drive(session_tmp_path):
- from mednet.libs.segmentation.scripts.view import view
+ from mednet.segment.scripts.view import view
runner = CliRunner()
@@ -385,11 +321,11 @@ def test_view_lwnet_drive(session_tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.drive")
def test_train_lwnet_drive_from_checkpoint(tmp_path):
- from mednet.libs.common.utils.checkpointer import (
+ from mednet.scripts.train import train
+ from mednet.utils.checkpointer import (
CHECKPOINT_EXTENSION,
_get_checkpoint_from_alias,
)
- from mednet.libs.segmentation.scripts.train import train
runner = CliRunner()
@@ -459,7 +395,7 @@ def test_train_lwnet_drive_from_checkpoint(tmp_path):
@pytest.mark.slow
@pytest.mark.skip_if_rc_var_not_set("datadir.drive")
def test_experiment(tmp_path):
- from mednet.libs.segmentation.scripts.experiment import experiment
+ from mednet.scripts.experiment import experiment
runner = CliRunner()
diff --git a/tests/segmentation/test_cxr8.py b/tests/segment/test_cxr8.py
similarity index 88%
rename from tests/segmentation/test_cxr8.py
rename to tests/segment/test_cxr8.py
index 756afb50..cadb8648 100644
--- a/tests/segmentation/test_cxr8.py
+++ b/tests/segment/test_cxr8.py
@@ -27,10 +27,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.cxr8", f"{split}.json.bz2"),
+ make_split("mednet.segment.config.data.cxr8", f"{split}.json.bz2"),
lengths=lengths,
prefixes=[],
possible_labels=[],
@@ -39,7 +39,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.cxr8")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["--limit=10", "cxr8"])
@@ -65,7 +65,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.segmentation.config.data.cxr8",
+ "mednet.segment.config.data.cxr8",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -97,7 +97,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".default",
- "mednet.libs.segmentation.config.data.cxr8",
+ "mednet.segment.config.data.cxr8",
).datamodule
datamodule.model_transforms = []
@@ -118,12 +118,12 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
datamodule = importlib.import_module(
".default",
- "mednet.libs.segmentation.config.data.cxr8",
+ "mednet.segment.config.data.cxr8",
).datamodule
model = importlib.import_module(
f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ "mednet.segment.config.models",
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_drhagis.py b/tests/segment/test_drhagis.py
similarity index 88%
rename from tests/segmentation/test_drhagis.py
rename to tests/segment/test_drhagis.py
index b18d1571..db571bbd 100644
--- a/tests/segmentation/test_drhagis.py
+++ b/tests/segment/test_drhagis.py
@@ -27,10 +27,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.drhagis", f"{split}.json"),
+ make_split("mednet.segment.config.data.drhagis", f"{split}.json"),
lengths=lengths,
prefixes=["Fundus_Images/"],
possible_labels=[],
@@ -39,7 +39,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.drhagis")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["drhagis"])
@@ -65,7 +65,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.segmentation.config.data.drhagis",
+ "mednet.segment.config.data.drhagis",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -97,7 +97,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".default",
- "mednet.libs.segmentation.config.data.drhagis",
+ "mednet.segment.config.data.drhagis",
).datamodule
datamodule.model_transforms = []
@@ -118,12 +118,12 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
datamodule = importlib.import_module(
".default",
- "mednet.libs.segmentation.config.data.drhagis",
+ "mednet.segment.config.data.drhagis",
).datamodule
model = importlib.import_module(
f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ "mednet.segment.config.models",
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_drionsdb.py b/tests/segment/test_drionsdb.py
similarity index 79%
rename from tests/segmentation/test_drionsdb.py
rename to tests/segment/test_drionsdb.py
index 81c77314..6d835269 100644
--- a/tests/segmentation/test_drionsdb.py
+++ b/tests/segment/test_drionsdb.py
@@ -28,10 +28,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.drionsdb", f"{split}.json"),
+ make_split("mednet.segment.config.data.drionsdb", f"{split}.json"),
lengths=lengths,
prefixes=["images/image_"],
possible_labels=[],
@@ -40,7 +40,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.drionsdb")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["drionsdb"])
@@ -50,24 +50,11 @@ def test_database_check():
@pytest.mark.skip_if_rc_var_not_set("datadir.drionsdb")
-@pytest.mark.parametrize(
- "dataset",
- [
- "train",
- "test",
- ],
-)
-@pytest.mark.parametrize(
- "name",
- [
- "expert1",
- "expert2",
- ],
-)
+@pytest.mark.parametrize("dataset", ["train", "test"])
+@pytest.mark.parametrize("name", ["expert1", "expert2"])
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
- f".{name}",
- "mednet.libs.segmentation.config.data.drionsdb",
+ f".{name}", "mednet.segment.config.data.drionsdb"
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -94,12 +81,11 @@ def test_loading(database_checkers, name: str, dataset: str):
@pytest.mark.skip_if_rc_var_not_set("datadir.drionsdb")
def test_raw_transforms_image_quality(database_checkers, datadir):
reference_histogram_file = str(
- datadir / "histograms/raw_data/histograms_drionsdb_expert1.json",
+ datadir / "histograms/raw_data/histograms_drionsdb_expert1.json"
)
datamodule = importlib.import_module(
- ".expert1",
- "mednet.libs.segmentation.config.data.drionsdb",
+ ".expert1", "mednet.segment.config.data.drionsdb"
).datamodule
datamodule.model_transforms = []
@@ -109,23 +95,18 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
@pytest.mark.skip_if_rc_var_not_set("datadir.drionsdb")
-@pytest.mark.parametrize(
- "model_name",
- ["lwnet"],
-)
+@pytest.mark.parametrize("model_name", ["lwnet"])
def test_model_transforms_image_quality(database_checkers, datadir, model_name):
reference_histogram_file = str(
datadir / f"histograms/models/histograms_{model_name}_drionsdb_expert1.json",
)
datamodule = importlib.import_module(
- ".expert1",
- "mednet.libs.segmentation.config.data.drionsdb",
+ ".expert1", "mednet.segment.config.data.drionsdb"
).datamodule
model = importlib.import_module(
- f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ f".{model_name}", "mednet.segment.config.models"
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_drishtigs1.py b/tests/segment/test_drishtigs1.py
similarity index 89%
rename from tests/segmentation/test_drishtigs1.py
rename to tests/segment/test_drishtigs1.py
index 5e4eb289..e49d79ba 100644
--- a/tests/segmentation/test_drishtigs1.py
+++ b/tests/segment/test_drishtigs1.py
@@ -28,10 +28,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.drishtigs1", f"{split}.json"),
+ make_split("mednet.segment.config.data.drishtigs1", f"{split}.json"),
lengths=lengths,
prefixes=[
"Drishti-GS1_files/Training/Images/drishtiGS_",
@@ -43,7 +43,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.drishtigs1")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["drishtigs1-disc-all"])
@@ -72,7 +72,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.segmentation.config.data.drishtigs1",
+ "mednet.segment.config.data.drishtigs1",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -107,7 +107,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".optic_cup_all",
- "mednet.libs.segmentation.config.data.drishtigs1",
+ "mednet.segment.config.data.drishtigs1",
).datamodule
datamodule.model_transforms = []
@@ -129,12 +129,12 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
datamodule = importlib.import_module(
".optic_cup_all",
- "mednet.libs.segmentation.config.data.drishtigs1",
+ "mednet.segment.config.data.drishtigs1",
).datamodule
model = importlib.import_module(
f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ "mednet.segment.config.models",
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_drive.py b/tests/segment/test_drive.py
similarity index 88%
rename from tests/segmentation/test_drive.py
rename to tests/segment/test_drive.py
index 59239042..de30a2d1 100644
--- a/tests/segmentation/test_drive.py
+++ b/tests/segment/test_drive.py
@@ -28,10 +28,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.drive", f"{split}.json"),
+ make_split("mednet.segment.config.data.drive", f"{split}.json"),
lengths=lengths,
prefixes=["training/", "test/"],
possible_labels=[],
@@ -40,7 +40,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.drive")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["drive"])
@@ -66,7 +66,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.segmentation.config.data.drive",
+ "mednet.segment.config.data.drive",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -98,7 +98,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".default",
- "mednet.libs.segmentation.config.data.drive",
+ "mednet.segment.config.data.drive",
).datamodule
datamodule.model_transforms = []
@@ -119,12 +119,12 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
datamodule = importlib.import_module(
".default",
- "mednet.libs.segmentation.config.data.drive",
+ "mednet.segment.config.data.drive",
).datamodule
model = importlib.import_module(
f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ "mednet.segment.config.models",
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_hrf.py b/tests/segment/test_hrf.py
similarity index 80%
rename from tests/segmentation/test_hrf.py
rename to tests/segment/test_hrf.py
index fafd1ba1..c8548ad1 100644
--- a/tests/segmentation/test_hrf.py
+++ b/tests/segment/test_hrf.py
@@ -27,10 +27,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.hrf", f"{split}.json"),
+ make_split("mednet.segment.config.data.hrf", f"{split}.json"),
lengths=lengths,
prefixes=["images/"],
possible_labels=[],
@@ -39,7 +39,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.hrf")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["hrf"])
@@ -49,23 +49,14 @@ def test_database_check():
@pytest.mark.skip_if_rc_var_not_set("datadir.hrf")
-@pytest.mark.parametrize(
- "dataset",
- [
- "train",
- "test",
- ],
-)
+@pytest.mark.parametrize("dataset", ["train", "test"])
@pytest.mark.parametrize(
"name",
- [
- "default",
- ],
+ ["default"],
)
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
- f".{name}",
- "mednet.libs.segmentation.config.data.hrf",
+ f".{name}", "mednet.segment.config.data.hrf"
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -96,8 +87,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
)
datamodule = importlib.import_module(
- ".default",
- "mednet.libs.segmentation.config.data.hrf",
+ ".default", "mednet.segment.config.data.hrf"
).datamodule
datamodule.model_transforms = []
@@ -107,23 +97,18 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
@pytest.mark.skip_if_rc_var_not_set("datadir.hrf")
-@pytest.mark.parametrize(
- "model_name",
- ["lwnet"],
-)
+@pytest.mark.parametrize("model_name", ["lwnet"])
def test_model_transforms_image_quality(database_checkers, datadir, model_name):
reference_histogram_file = str(
datadir / f"histograms/models/histograms_{model_name}_hrf_default.json",
)
datamodule = importlib.import_module(
- ".default",
- "mednet.libs.segmentation.config.data.hrf",
+ ".default", "mednet.segment.config.data.hrf"
).datamodule
model = importlib.import_module(
- f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ f".{model_name}", "mednet.segment.config.models"
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_iostar.py b/tests/segment/test_iostar.py
similarity index 88%
rename from tests/segmentation/test_iostar.py
rename to tests/segment/test_iostar.py
index 3776513b..f924191a 100644
--- a/tests/segmentation/test_iostar.py
+++ b/tests/segment/test_iostar.py
@@ -28,10 +28,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.iostar", f"{split}.json"),
+ make_split("mednet.segment.config.data.iostar", f"{split}.json"),
lengths=lengths,
prefixes=["image/STAR "],
possible_labels=[],
@@ -40,7 +40,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.iostar")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["iostar-vessel"])
@@ -64,7 +64,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.segmentation.config.data.iostar",
+ "mednet.segment.config.data.iostar",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -96,7 +96,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".vessel",
- "mednet.libs.segmentation.config.data.iostar",
+ "mednet.segment.config.data.iostar",
).datamodule
datamodule.model_transforms = []
@@ -117,12 +117,12 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
datamodule = importlib.import_module(
".vessel",
- "mednet.libs.segmentation.config.data.iostar",
+ "mednet.segment.config.data.iostar",
).datamodule
model = importlib.import_module(
f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ "mednet.segment.config.models",
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_jsrt.py b/tests/segment/test_jsrt.py
similarity index 77%
rename from tests/segmentation/test_jsrt.py
rename to tests/segment/test_jsrt.py
index a792994f..38a13675 100644
--- a/tests/segmentation/test_jsrt.py
+++ b/tests/segment/test_jsrt.py
@@ -17,9 +17,7 @@ def id_function(val):
@pytest.mark.parametrize(
"split,lengths",
- [
- ("default", dict(train=172, validation=25, test=50)),
- ],
+ [("default", dict(train=172, validation=25, test=50))],
ids=id_function, # just changes how pytest prints it
)
def test_protocol_consistency(
@@ -27,10 +25,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.jsrt", f"{split}.json"),
+ make_split("mednet.segment.config.data.jsrt", f"{split}.json"),
lengths=lengths,
prefixes=["All247images/JPC"],
possible_labels=[],
@@ -39,7 +37,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.jsrt")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["jsrt"])
@@ -49,24 +47,11 @@ def test_database_check():
@pytest.mark.skip_if_rc_var_not_set("datadir.jsrt")
-@pytest.mark.parametrize(
- "dataset",
- [
- "train",
- "validation",
- "test",
- ],
-)
-@pytest.mark.parametrize(
- "name",
- [
- "default",
- ],
-)
+@pytest.mark.parametrize("dataset", ["train", "validation", "test"])
+@pytest.mark.parametrize("name", ["default"])
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
- f".{name}",
- "mednet.libs.segmentation.config.data.jsrt",
+ f".{name}", "mednet.segment.config.data.jsrt"
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -97,8 +82,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
)
datamodule = importlib.import_module(
- ".default",
- "mednet.libs.segmentation.config.data.jsrt",
+ ".default", "mednet.segment.config.data.jsrt"
).datamodule
datamodule.model_transforms = []
@@ -108,23 +92,18 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
@pytest.mark.skip_if_rc_var_not_set("datadir.jsrt")
-@pytest.mark.parametrize(
- "model_name",
- ["lwnet"],
-)
+@pytest.mark.parametrize("model_name", ["lwnet"])
def test_model_transforms_image_quality(database_checkers, datadir, model_name):
reference_histogram_file = str(
datadir / f"histograms/models/histograms_{model_name}_jsrt_default.json",
)
datamodule = importlib.import_module(
- ".default",
- "mednet.libs.segmentation.config.data.jsrt",
+ ".default", "mednet.segment.config.data.jsrt"
).datamodule
model = importlib.import_module(
- f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ f".{model_name}", "mednet.segment.config.models"
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_measures.py b/tests/segment/test_measures.py
similarity index 90%
rename from tests/segmentation/test_measures.py
rename to tests/segment/test_measures.py
index cfc9db1d..239f0509 100644
--- a/tests/segmentation/test_measures.py
+++ b/tests/segment/test_measures.py
@@ -5,7 +5,7 @@
import random
import numpy
-from mednet.libs.segmentation.engine.evaluator import all_metrics
+from mednet.segment.engine.evaluator import all_metrics
def test_all_metrics():
diff --git a/tests/segmentation/test_montgomery.py b/tests/segment/test_montgomery.py
similarity index 88%
rename from tests/segmentation/test_montgomery.py
rename to tests/segment/test_montgomery.py
index cb6223ac..b2fc0ffb 100644
--- a/tests/segmentation/test_montgomery.py
+++ b/tests/segment/test_montgomery.py
@@ -27,10 +27,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.montgomery", f"{split}.json"),
+ make_split("mednet.segment.config.data.montgomery", f"{split}.json"),
lengths=lengths,
prefixes=["CXR_png"],
possible_labels=[],
@@ -39,7 +39,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["montgomery"])
@@ -66,7 +66,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.segmentation.config.data.montgomery",
+ "mednet.segment.config.data.montgomery",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -98,7 +98,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".default",
- "mednet.libs.segmentation.config.data.montgomery",
+ "mednet.segment.config.data.montgomery",
).datamodule
datamodule.model_transforms = []
@@ -119,12 +119,12 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
datamodule = importlib.import_module(
".default",
- "mednet.libs.segmentation.config.data.montgomery",
+ "mednet.segment.config.data.montgomery",
).datamodule
model = importlib.import_module(
f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ "mednet.segment.config.models",
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_refuge.py b/tests/segment/test_refuge.py
similarity index 84%
rename from tests/segmentation/test_refuge.py
rename to tests/segment/test_refuge.py
index 14b04b69..ec4b1c4a 100644
--- a/tests/segmentation/test_refuge.py
+++ b/tests/segment/test_refuge.py
@@ -27,10 +27,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.refuge", f"{split}.json"),
+ make_split("mednet.segment.config.data.refuge", f"{split}.json"),
lengths=lengths,
prefixes=["Training400/", "REFUGE-Validation400/V", "Test400/T0"],
possible_labels=[],
@@ -39,7 +39,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.refuge")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["--limit=10", "refuge-disc"])
@@ -51,23 +51,16 @@ def test_database_check():
@pytest.mark.skip_if_rc_var_not_set("datadir.refuge")
@pytest.mark.parametrize(
"dataset",
- [
- "train",
- "validation",
- "test",
- ],
+ ["train", "validation", "test"],
)
@pytest.mark.parametrize(
"name",
- [
- "cup",
- "disc",
- ],
+ ["cup", "disc"],
)
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.segmentation.config.data.refuge",
+ "mednet.segment.config.data.refuge",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -98,8 +91,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
)
datamodule = importlib.import_module(
- ".cup",
- "mednet.libs.segmentation.config.data.refuge",
+ ".cup", "mednet.segment.config.data.refuge"
).datamodule
datamodule.model_transforms = []
@@ -119,13 +111,11 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
)
datamodule = importlib.import_module(
- ".cup",
- "mednet.libs.segmentation.config.data.refuge",
+ ".cup", "mednet.segment.config.data.refuge"
).datamodule
model = importlib.import_module(
- f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ f".{model_name}", "mednet.segment.config.models"
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_rimoner3.py b/tests/segment/test_rimoner3.py
similarity index 89%
rename from tests/segmentation/test_rimoner3.py
rename to tests/segment/test_rimoner3.py
index 2a5bde70..3c784666 100644
--- a/tests/segmentation/test_rimoner3.py
+++ b/tests/segment/test_rimoner3.py
@@ -30,10 +30,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.rimoner3", f"{split}.json"),
+ make_split("mednet.segment.config.data.rimoner3", f"{split}.json"),
lengths=lengths,
prefixes=["Healthy/Stereo Images/N-", "Glaucoma and suspects/Stereo Images/"],
possible_labels=[],
@@ -42,7 +42,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.rimoner3")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["rimoner3-cup"])
@@ -71,7 +71,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.segmentation.config.data.rimoner3",
+ "mednet.segment.config.data.rimoner3",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -106,7 +106,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".cup_exp1",
- "mednet.libs.segmentation.config.data.rimoner3",
+ "mednet.segment.config.data.rimoner3",
).datamodule
datamodule.model_transforms = []
@@ -127,12 +127,12 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
datamodule = importlib.import_module(
".cup_exp1",
- "mednet.libs.segmentation.config.data.rimoner3",
+ "mednet.segment.config.data.rimoner3",
).datamodule
model = importlib.import_module(
f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ "mednet.segment.config.models",
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_shenzhen.py b/tests/segment/test_shenzhen.py
similarity index 88%
rename from tests/segmentation/test_shenzhen.py
rename to tests/segment/test_shenzhen.py
index 71ea78f2..0083262d 100644
--- a/tests/segmentation/test_shenzhen.py
+++ b/tests/segment/test_shenzhen.py
@@ -27,10 +27,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.shenzhen", f"{split}.json"),
+ make_split("mednet.segment.config.data.shenzhen", f"{split}.json"),
lengths=lengths,
prefixes=["CXR_png/CHNCXR_"],
possible_labels=[],
@@ -39,7 +39,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.shenzhen")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["--limit=20", "shenzhen"])
@@ -66,7 +66,7 @@ def test_database_check():
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
f".{name}",
- "mednet.libs.segmentation.config.data.shenzhen",
+ "mednet.segment.config.data.shenzhen",
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -98,7 +98,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
datamodule = importlib.import_module(
".default",
- "mednet.libs.segmentation.config.data.shenzhen",
+ "mednet.segment.config.data.shenzhen",
).datamodule
datamodule.model_transforms = []
@@ -119,12 +119,12 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
datamodule = importlib.import_module(
".default",
- "mednet.libs.segmentation.config.data.shenzhen",
+ "mednet.segment.config.data.shenzhen",
).datamodule
model = importlib.import_module(
f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ "mednet.segment.config.models",
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/test_stare.py b/tests/segment/test_stare.py
similarity index 82%
rename from tests/segmentation/test_stare.py
rename to tests/segment/test_stare.py
index 6b6307d8..f4f95605 100644
--- a/tests/segmentation/test_stare.py
+++ b/tests/segment/test_stare.py
@@ -28,10 +28,10 @@ def test_protocol_consistency(
split: str,
lengths: dict[str, int],
):
- from mednet.libs.common.data.split import make_split
+ from mednet.data.split import make_split
database_checkers.check_split(
- make_split("mednet.libs.segmentation.config.data.stare", f"{split}.json"),
+ make_split("mednet.segment.config.data.stare", f"{split}.json"),
lengths=lengths,
prefixes=["stare-images/im0"],
possible_labels=[],
@@ -40,7 +40,7 @@ def test_protocol_consistency(
@pytest.mark.skip_if_rc_var_not_set("datadir.stare")
def test_database_check():
- from mednet.libs.segmentation.scripts.database import check
+ from mednet.scripts.database import check
runner = CliRunner()
result = runner.invoke(check, ["stare"])
@@ -52,22 +52,15 @@ def test_database_check():
@pytest.mark.skip_if_rc_var_not_set("datadir.stare")
@pytest.mark.parametrize(
"dataset",
- [
- "train",
- "test",
- ],
+ ["train", "test"],
)
@pytest.mark.parametrize(
"name",
- [
- "ah",
- "vk",
- ],
+ ["ah", "vk"],
)
def test_loading(database_checkers, name: str, dataset: str):
datamodule = importlib.import_module(
- f".{name}",
- "mednet.libs.segmentation.config.data.stare",
+ f".{name}", "mednet.segment.config.data.stare"
).datamodule
datamodule.model_transforms = [] # should be done before setup()
@@ -98,8 +91,7 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
)
datamodule = importlib.import_module(
- ".ah",
- "mednet.libs.segmentation.config.data.stare",
+ ".ah", "mednet.segment.config.data.stare"
).datamodule
datamodule.model_transforms = []
@@ -109,23 +101,18 @@ def test_raw_transforms_image_quality(database_checkers, datadir):
@pytest.mark.skip_if_rc_var_not_set("datadir.stare")
-@pytest.mark.parametrize(
- "model_name",
- ["lwnet"],
-)
+@pytest.mark.parametrize("model_name", ["lwnet"])
def test_model_transforms_image_quality(database_checkers, datadir, model_name):
reference_histogram_file = str(
datadir / f"histograms/models/histograms_{model_name}_stare_ah.json",
)
datamodule = importlib.import_module(
- ".ah",
- "mednet.libs.segmentation.config.data.stare",
+ ".ah", "mednet.segment.config.data.stare"
).datamodule
model = importlib.import_module(
- f".{model_name}",
- "mednet.libs.segmentation.config.models",
+ f".{model_name}", "mednet.segment.config.models"
).model
datamodule.model_transforms = model.model_transforms
diff --git a/tests/segmentation/__init__.py b/tests/segmentation/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/tests/test_cli.py b/tests/test_cli.py
index abed41d2..3dacef8e 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -53,7 +53,98 @@ def test_info():
assert "platform:" in result.output
assert "accelerators:" in result.output
assert "version:" in result.output
- assert "configured classification databases:" in result.output
- assert "configured segmentation databases:" in result.output
+ assert "databases:" in result.output
assert "dependencies:" in result.output
assert "python:" in result.output
+
+
+def test_config_help():
+ from mednet.scripts.config import config
+
+ _check_help(config)
+
+
+def test_config_list_help():
+ from mednet.scripts.config import list_
+
+ _check_help(list_)
+
+
+def test_config_list():
+ from mednet.scripts.config import list_
+
+ runner = CliRunner()
+ result = runner.invoke(list_)
+ _assert_exit_0(result)
+ assert "module: mednet.classify.config.data" in result.output
+ assert "module: mednet.classify.config.models" in result.output
+ assert "module: mednet.segment.config.data" in result.output
+ assert "module: mednet.segment.config.models" in result.output
+
+
+def test_config_list_v():
+ from mednet.scripts.config import list_
+
+ result = CliRunner().invoke(list_, ["--verbose"])
+ _assert_exit_0(result)
+ assert "module: mednet.classify.config.data" in result.output
+ assert "module: mednet.classify.config.models" in result.output
+ assert "module: mednet.segment.config.data" in result.output
+ assert "module: mednet.segment.config.models" in result.output
+
+
+def test_config_describe_help():
+ from mednet.scripts.config import describe
+
+ _check_help(describe)
+
+
+def test_database_help():
+ from mednet.scripts.database import database
+
+ _check_help(database)
+
+
+def test_database_list_help():
+ from mednet.scripts.database import list_
+
+ _check_help(list_)
+
+
+def test_database_list():
+ from mednet.scripts.database import list_
+
+ runner = CliRunner()
+ result = runner.invoke(list_)
+ _assert_exit_0(result)
+ assert result.output.startswith(" - ")
+
+
+def test_database_check_help():
+ from mednet.scripts.database import check
+
+ _check_help(check)
+
+
+def test_train_help():
+ from mednet.scripts.train import train
+
+ _check_help(train)
+
+
+def test_predict_help():
+ from mednet.scripts.predict import predict
+
+ _check_help(predict)
+
+
+def test_experiment_help():
+ from mednet.scripts.experiment import experiment
+
+ _check_help(experiment)
+
+
+def test_upload_help():
+ from mednet.scripts.upload import upload
+
+ _check_help(upload)
diff --git a/tests/test_database_split.py b/tests/test_database_split.py
index 114dd1ba..8f50ed99 100644
--- a/tests/test_database_split.py
+++ b/tests/test_database_split.py
@@ -3,7 +3,7 @@
# SPDX-License-Identifier: GPL-3.0-or-later
"""Test code for datasets."""
-from mednet.libs.common.data.split import JSONDatabaseSplit
+from mednet.data.split import JSONDatabaseSplit
def test_json_loading(datadir):
diff --git a/tests/test_image_utils.py b/tests/test_image_utils.py
index 6ba40ef1..ab431eca 100644
--- a/tests/test_image_utils.py
+++ b/tests/test_image_utils.py
@@ -5,7 +5,7 @@
import numpy
import PIL.Image
-from mednet.libs.common.data.image_utils import remove_black_borders
+from mednet.data.image_utils import remove_black_borders
def test_remove_black_borders(datadir):
diff --git a/tests/test_resource_monitor.py b/tests/test_resource_monitor.py
index ed409590..028932ce 100644
--- a/tests/test_resource_monitor.py
+++ b/tests/test_resource_monitor.py
@@ -13,7 +13,7 @@ import pytest
def test_cpu_constants():
- from mednet.libs.common.utils.resources import cpu_constants
+ from mednet.utils.resources import cpu_constants
v = cpu_constants()
assert "memory-total-GB/cpu" in v
@@ -21,8 +21,8 @@ def test_cpu_constants():
def test_combined_monitor_cpu_only():
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.utils.resources import _CombinedMonitor
+ from mednet.engine.device import DeviceManager
+ from mednet.utils.resources import _CombinedMonitor
monitor = _CombinedMonitor(
device_type=DeviceManager("cpu").device_type,
@@ -48,7 +48,7 @@ def test_combined_monitor_cpu_only():
reason="Requires macOS on Apple silicon to run",
)
def test_mps_constants():
- from mednet.libs.common.utils.resources import mps_constants
+ from mednet.utils.resources import mps_constants
v = mps_constants()
assert "apple-processor-model" in v
@@ -60,8 +60,8 @@ def test_mps_constants():
reason="Requires macOS on Apple silicon to run",
)
def test_combined_monitor_macos_gpu():
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.utils.resources import _CombinedMonitor
+ from mednet.engine.device import DeviceManager
+ from mednet.utils.resources import _CombinedMonitor
monitor = _CombinedMonitor(
device_type=DeviceManager("mps").device_type,
@@ -90,7 +90,7 @@ def test_combined_monitor_macos_gpu():
shutil.which("nvidia-smi") is None, reason="Requires nvidia-smi to run"
)
def test_cuda_constants():
- from mednet.libs.common.utils.resources import cuda_constants
+ from mednet.utils.resources import cuda_constants
v = cuda_constants()
assert "driver-version/gpu" in v
@@ -101,8 +101,8 @@ def test_cuda_constants():
shutil.which("nvidia-smi") is None, reason="Requires nvidia-smi to run"
)
def test_combined_monitor_nvidia_gpu():
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.utils.resources import _CombinedMonitor
+ from mednet.engine.device import DeviceManager
+ from mednet.utils.resources import _CombinedMonitor
monitor = _CombinedMonitor(
device_type=DeviceManager("cuda").device_type,
@@ -130,8 +130,8 @@ def test_combined_monitor_nvidia_gpu():
def test_aggregation():
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.utils.resources import _CombinedMonitor, aggregate
+ from mednet.engine.device import DeviceManager
+ from mednet.utils.resources import _CombinedMonitor, aggregate
monitor = _CombinedMonitor(
device_type=DeviceManager("cpu").device_type,
@@ -168,8 +168,8 @@ def test_mp_cpu_monitoring():
# Checks a "normal" workflow, where the monitoring interval is smaller than
# the total work time
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.utils.resources import ResourceMonitor, aggregate
+ from mednet.engine.device import DeviceManager
+ from mednet.utils.resources import ResourceMonitor, aggregate
rm = ResourceMonitor(
interval=0.2,
@@ -189,8 +189,8 @@ def test_mp_cpu_monitoring_short_processing():
# Checks we can get at least 1 monitoring sample even if the processing is
# super short
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.utils.resources import ResourceMonitor, aggregate
+ from mednet.engine.device import DeviceManager
+ from mednet.utils.resources import ResourceMonitor, aggregate
rm = ResourceMonitor(
interval=0.5,
@@ -214,8 +214,8 @@ def test_mp_macos_gpu_monitoring():
# Checks a "normal" workflow, where the monitoring interval is smaller than
# the total work time
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.utils.resources import ResourceMonitor, aggregate
+ from mednet.engine.device import DeviceManager
+ from mednet.utils.resources import ResourceMonitor, aggregate
rm = ResourceMonitor(
interval=1.5,
@@ -240,8 +240,8 @@ def test_mp_macos_gpu_monitoring_short_processing():
# shorter. In this check we execute an external utility which may
# delay obtaining samples.
- from mednet.libs.common.engine.device import DeviceManager
- from mednet.libs.common.utils.resources import ResourceMonitor, aggregate
+ from mednet.engine.device import DeviceManager
+ from mednet.utils.resources import ResourceMonitor, aggregate
rm = ResourceMonitor(
interval=1.5, # on my mac, this measurements take ~0.9s
diff --git a/tests/test_transforms.py b/tests/test_transforms.py
index 33e80bb9..8bbfc850 100644
--- a/tests/test_transforms.py
+++ b/tests/test_transforms.py
@@ -7,8 +7,8 @@ import numpy
import PIL.Image
import torch
import torchvision.transforms.functional as F # noqa: N812
-from mednet.libs.common.data.augmentations import ElasticDeformation
-from mednet.libs.common.models.transforms import crop_image_to_mask
+from mednet.data.augmentations import ElasticDeformation
+from mednet.models.transforms import crop_image_to_mask
def test_crop_mask():
--
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