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Commit 819a4380 authored by André Anjos's avatar André Anjos :speech_balloon:
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[data.indian] Re-structure database to new format; Uncompress json files for easier maintenance

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src/ptbench/data/indian/__init__.py
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# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Indian collection dataset for computer-aided diagnosis.
The Indian collection database has been established to foster research
in computer-aided diagnosis of pulmonary diseases with a special
focus on pulmonary tuberculosis (TB).
* Reference: [INDIAN-2013]_
* Original resolution (height x width or width x height): more than 1024 x 1024
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
"""
import importlib.resources
import os
from ...utils.rc import load_rc
from .. import make_dataset
from ..dataset import JSONDataset
from ..loader import load_pil_grayscale, make_delayed
_protocols = [
importlib.resources.files(__name__).joinpath("default.json.bz2"),
importlib.resources.files(__name__).joinpath("fold_0.json.bz2"),
importlib.resources.files(__name__).joinpath("fold_1.json.bz2"),
importlib.resources.files(__name__).joinpath("fold_2.json.bz2"),
importlib.resources.files(__name__).joinpath("fold_3.json.bz2"),
importlib.resources.files(__name__).joinpath("fold_4.json.bz2"),
importlib.resources.files(__name__).joinpath("fold_5.json.bz2"),
importlib.resources.files(__name__).joinpath("fold_6.json.bz2"),
importlib.resources.files(__name__).joinpath("fold_7.json.bz2"),
importlib.resources.files(__name__).joinpath("fold_8.json.bz2"),
importlib.resources.files(__name__).joinpath("fold_9.json.bz2"),
]
_datadir = load_rc().get("datadir.indian", os.path.realpath(os.curdir))
def _raw_data_loader(sample):
return dict(
data=load_pil_grayscale(os.path.join(_datadir, sample["data"])),
label=sample["label"],
)
def _loader(context, sample):
# "context" is ignored in this case - database is homogeneous
# we returned delayed samples to avoid loading all images at once
return make_delayed(sample, _raw_data_loader)
json_dataset = JSONDataset(
protocols=_protocols,
fieldnames=("data", "label"),
loader=_loader,
)
"""Indian dataset object."""
def _maker(protocol, resize_size=512, cc_size=512, RGB=False):
from torchvision import transforms
from ..augmentations import ElasticDeformation
from ..image_utils import RemoveBlackBorders
post_transforms = []
if RGB:
post_transforms = [
transforms.Lambda(lambda x: x.convert("RGB")),
transforms.ToTensor(),
]
return make_dataset(
[json_dataset.subsets(protocol)],
[
RemoveBlackBorders(),
transforms.Resize(resize_size),
transforms.CenterCrop(cc_size),
],
[ElasticDeformation(p=0.8)],
post_transforms,
)
src/ptbench/data/indian/datamodule.py 0 → 100644
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# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
import importlib.resources
from ..datamodule import CachingDataModule
from ..shenzhen.datamodule import RawDataLoader
from ..split import JSONDatabaseSplit
class DataModule(CachingDataModule):
"""Indian collection dataset for computer-aided diagnosis.
The Indian collection database has been established to foster research
in computer-aided diagnosis of pulmonary diseases with a special
focus on pulmonary tuberculosis (TB).
* Original resolution (height x width or width x height): more than 1024 x 1024
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
Data specifications:
* Raw data input (on disk):
* PNG images (grayscale, encoded as RGB images with "inverted" grayscale scale)
* Variable width and height
* Output image:
* Transforms:
* Load raw PNG with :py:mod:`PIL`
* Remove black borders
* Torch center cropping to get square image
* Final specifications:
* Grayscale, encoded as a single plane image, 8 bits
* Square, with varying resolutions, depending on the input image
"""
def __init__(self, split_filename: str):
super().__init__(
database_split=JSONDatabaseSplit(
importlib.resources.files(__name__.rsplit(".", 1)[0]).joinpath(
split_filename
)
),
raw_data_loader=RawDataLoader(),
)
src/ptbench/data/indian/datamodules.py deleted 100644 → 0
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# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (default protocol)
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class DefaultModule(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("default")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = DefaultModule
src/ptbench/data/indian/default.json 0 → 100644
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{
"train": [
["DatasetA/Training/nx52.jpg", 0],
["DatasetA/Training/nx19.jpg", 0],
["DatasetA/Training/nx38.jpg", 0],
["DatasetA/Training/nx39.jpg", 0],
["DatasetA/Training/nx35.jpg", 0],
["DatasetA/Training/nx21.jpg", 0],
["DatasetA/Training/nx20.jpg", 0],
["DatasetA/Training/nx11.jpg", 0],
["DatasetA/Training/nx34.jpg", 0],
["DatasetA/Training/nx13.jpg", 0],
["DatasetA/Training/nx12.jpg", 0],
["DatasetA/Training/nx22.jpg", 0],
["DatasetA/Training/nx36.jpg", 0],
["DatasetA/Training/nx16.jpg", 0],
["DatasetA/Training/nx37.jpg", 0],
["DatasetA/Training/nx17.jpg", 0],
["DatasetA/Training/nx29.jpg", 0],
["DatasetA/Training/nx27.jpg", 0],
["DatasetA/Training/nx15.jpg", 0],
["DatasetA/Training/nx33.jpg", 0],
["DatasetA/Training/nx14.jpg", 0],
["DatasetA/Training/nx32.jpg", 0],
["DatasetA/Training/nx26.jpg", 0],
["DatasetA/Training/nx28.jpg", 0],
["DatasetA/Training/nx30.jpg", 0],
["DatasetA/Training/nx31.jpg", 0],
["DatasetA/Training/nx24.jpg", 0],
["DatasetA/Training/nx18.jpg", 0],
["DatasetA/Training/nx46.jpg", 0],
["DatasetA/Training/nx7.jpg", 0],
["DatasetA/Training/nx25.jpg", 0],
["DatasetA/Training/nx47.jpg", 0],
["DatasetA/Training/nx41.jpg", 0],
["DatasetA/Training/nx1.jpg", 0],
["DatasetA/Training/nx40.jpg", 0],
["DatasetA/Training/nx6.jpg", 0],
["DatasetA/Training/nx49.jpg", 0],
["DatasetA/Training/nx8.jpg", 0],
["DatasetA/Training/nx9.jpg", 0],
["DatasetA/Training/nx48.jpg", 0],
["DatasetA/Training/nx44.jpg", 0],
["DatasetA/Training/px45.jpg", 1],
["DatasetA/Training/px51.jpg", 1],
["DatasetA/Training/px48.jpg", 1],
["DatasetA/Training/px10.jpg", 1],
["DatasetA/Training/px38.jpg", 1],
["DatasetA/Training/px15.jpg", 1],
["DatasetA/Training/px11.jpg", 1],
["DatasetA/Training/px29.jpg", 1],
["DatasetA/Training/px49.jpg", 1],
["DatasetA/Training/px14.jpg", 1],
["DatasetA/Training/px8.jpg", 1],
["DatasetA/Training/px28.jpg", 1],
["DatasetA/Training/px9.jpg", 1],
["DatasetA/Training/px16.jpg", 1],
["DatasetA/Training/px17.jpg", 1],
["DatasetA/Training/px39.jpg", 1],
["DatasetA/Training/px22.jpg", 1],
["DatasetA/Training/px47.jpg", 1],
["DatasetA/Training/px50.jpg", 1],
["DatasetA/Training/px36.jpg", 1],
["DatasetA/Training/px37.jpg", 1],
["DatasetA/Training/px23.jpg", 1],
["DatasetA/Training/px35.jpg", 1],
["DatasetA/Training/px21.jpg", 1],
["DatasetA/Training/px20.jpg", 1],
["DatasetA/Training/px34.jpg", 1],
["DatasetA/Training/px30.jpg", 1],
["DatasetA/Training/px24.jpg", 1],
["DatasetA/Training/px18.jpg", 1],
["DatasetA/Training/px19.jpg", 1],
["DatasetA/Training/px25.jpg", 1],
["DatasetA/Training/px31.jpg", 1],
["DatasetA/Training/px27.jpg", 1],
["DatasetA/Training/px33.jpg", 1],
["DatasetA/Training/px32.jpg", 1],
["DatasetA/Training/px26.jpg", 1],
["DatasetA/Training/px44.jpg", 1],
["DatasetA/Training/px52.jpg", 1],
["DatasetA/Training/px46.jpg", 1],
["DatasetA/Training/px3.jpg", 1],
["DatasetA/Training/px2.jpg", 1],
["DatasetA/Training/px12.jpg", 1]
],
"validation": [
["DatasetA/Training/nx43.jpg", 0],
["DatasetA/Training/nx50.jpg", 0],
["DatasetA/Training/nx4.jpg", 0],
["DatasetA/Training/nx51.jpg", 0],
["DatasetA/Training/nx45.jpg", 0],
["DatasetA/Training/nx2.jpg", 0],
["DatasetA/Training/nx3.jpg", 0],
["DatasetA/Training/nx42.jpg", 0],
["DatasetA/Training/nx10.jpg", 0],
["DatasetA/Training/nx5.jpg", 0],
["DatasetA/Training/px1.jpg", 1],
["DatasetA/Training/px43.jpg", 1],
["DatasetA/Training/px7.jpg", 1],
["DatasetA/Training/px42.jpg", 1],
["DatasetA/Training/px40.jpg", 1],
["DatasetA/Training/px5.jpg", 1],
["DatasetA/Training/px4.jpg", 1],
["DatasetA/Training/px41.jpg", 1],
["DatasetA/Training/px6.jpg", 1],
["DatasetA/Training/px13.jpg", 1]
],
"test": [
["DatasetA/Testing/nx26.jpg", 0],
["DatasetA/Testing/nx19.jpg", 0],
["DatasetA/Testing/nx25.jpg", 0],
["DatasetA/Testing/nx14.jpg", 0],
["DatasetA/Testing/nx15.jpg", 0],
["DatasetA/Testing/nx23.jpg", 0],
["DatasetA/Testing/nx22.jpg", 0],
["DatasetA/Testing/nx17.jpg", 0],
["DatasetA/Testing/nx20.jpg", 0],
["DatasetA/Testing/nx21.jpg", 0],
["DatasetA/Testing/nx16.jpg", 0],
["DatasetA/Testing/nx24.jpg", 0],
["DatasetA/Testing/nx7.jpg", 0],
["DatasetA/Testing/nx12.jpg", 0],
["DatasetA/Testing/nx13.jpg", 0],
["DatasetA/Testing/nx3.jpg", 0],
["DatasetA/Testing/nx2.jpg", 0],
["DatasetA/Testing/nx8.jpg", 0],
["DatasetA/Testing/nx6.jpg", 0],
["DatasetA/Testing/nx9.jpg", 0],
["DatasetA/Testing/nx1.jpg", 0],
["DatasetA/Testing/nx5.jpg", 0],
["DatasetA/Testing/nx4.jpg", 0],
["DatasetA/Testing/nx10.jpg", 0],
["DatasetA/Testing/nx11.jpg", 0],
["DatasetA/Testing/nx18.jpg", 0],
["DatasetA/Testing/px28.jpg", 1],
["DatasetA/Testing/px29.jpg", 1],
["DatasetA/Testing/px48.jpg", 1],
["DatasetA/Testing/px45.jpg", 1],
["DatasetA/Testing/px51.jpg", 1],
["DatasetA/Testing/px49.jpg", 1],
["DatasetA/Testing/px36.jpg", 1],
["DatasetA/Testing/px44.jpg", 1],
["DatasetA/Testing/px37.jpg", 1],
["DatasetA/Testing/px35.jpg", 1],
["DatasetA/Testing/px34.jpg", 1],
["DatasetA/Testing/px30.jpg", 1],
["DatasetA/Testing/px31.jpg", 1],
["DatasetA/Testing/px27.jpg", 1],
["DatasetA/Testing/px33.jpg", 1],
["DatasetA/Testing/px50.jpg", 1],
["DatasetA/Testing/px32.jpg", 1],
["DatasetA/Testing/px40.jpg", 1],
["DatasetA/Testing/px42.jpg", 1],
["DatasetA/Testing/px43.jpg", 1],
["DatasetA/Testing/px47.jpg", 1],
["DatasetA/Testing/px39.jpg", 1],
["DatasetA/Testing/px46.jpg", 1],
["DatasetA/Testing/px52.jpg", 1],
["DatasetA/Testing/px41.jpg", 1],
["DatasetA/Testing/px38.jpg", 1]
]
}
src/ptbench/data/indian/default.json.bz2 deleted 100644 → 0
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src/ptbench/data/indian/default.py 0 → 100644
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# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
#
# SPDX-License-Identifier: GPL-3.0-or-later
from .datamodule import DataModule
datamodule = DataModule("default.json.bz2")
src/ptbench/data/indian/fold_0.json 0 → 100644
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{
"train": [
["DatasetA/Training/nx19.jpg", 0],
["DatasetA/Training/nx35.jpg", 0],
["DatasetA/Training/nx32.jpg", 0],
["DatasetA/Testing/nx17.jpg", 0],
["DatasetA/Testing/nx19.jpg", 0],
["DatasetA/Training/nx45.jpg", 0],
["DatasetA/Training/nx14.jpg", 0],
["DatasetA/Training/px27.jpg", 1],
["DatasetA/Training/px3.jpg", 1],
["DatasetA/Testing/nx8.jpg", 0],
["DatasetA/Training/nx16.jpg", 0],
["DatasetA/Training/px35.jpg", 1],
["DatasetA/Training/px49.jpg", 1],
["DatasetA/Training/px39.jpg", 1],
["DatasetA/Testing/nx21.jpg", 0],
["DatasetA/Testing/nx13.jpg", 0],
["DatasetA/Testing/nx23.jpg", 0],
["DatasetA/Training/nx1.jpg", 0],
["DatasetA/Training/nx38.jpg", 0],
["DatasetA/Testing/px35.jpg", 1],
["DatasetA/Training/px31.jpg", 1],
["DatasetA/Training/px15.jpg", 1],
["DatasetA/Training/px6.jpg", 1],
["DatasetA/Training/px7.jpg", 1],
["DatasetA/Training/nx40.jpg", 0],
["DatasetA/Training/nx46.jpg", 0],
["DatasetA/Training/nx10.jpg", 0],
["DatasetA/Testing/nx16.jpg", 0],
["DatasetA/Training/nx47.jpg", 0],
["DatasetA/Training/px22.jpg", 1],
["DatasetA/Testing/nx18.jpg", 0],
["DatasetA/Testing/px40.jpg", 1],
["DatasetA/Testing/px33.jpg", 1],
["DatasetA/Testing/px38.jpg", 1],
["DatasetA/Testing/nx22.jpg", 0],
["DatasetA/Training/nx31.jpg", 0],
["DatasetA/Testing/px36.jpg", 1],
["DatasetA/Training/px38.jpg", 1],
["DatasetA/Training/px29.jpg", 1],
["DatasetA/Testing/px41.jpg", 1],
["DatasetA/Testing/nx25.jpg", 0],
["DatasetA/Testing/px44.jpg", 1],
["DatasetA/Training/px10.jpg", 1],
["DatasetA/Testing/nx5.jpg", 0],
["DatasetA/Training/px50.jpg", 1],
["DatasetA/Training/nx48.jpg", 0],
["DatasetA/Training/nx34.jpg", 0],
["DatasetA/Testing/nx24.jpg", 0],
["DatasetA/Testing/px31.jpg", 1],
["DatasetA/Training/px33.jpg", 1],
["DatasetA/Training/px34.jpg", 1],
["DatasetA/Testing/px52.jpg", 1],
["DatasetA/Training/px52.jpg", 1],
["DatasetA/Testing/px42.jpg", 1],
["DatasetA/Training/nx41.jpg", 0],
["DatasetA/Training/px41.jpg", 1],
["DatasetA/Training/px14.jpg", 1],
["DatasetA/Testing/px37.jpg", 1],
["DatasetA/Testing/px48.jpg", 1],
["DatasetA/Training/px8.jpg", 1],
["DatasetA/Training/nx37.jpg", 0],
["DatasetA/Training/nx51.jpg", 0],
["DatasetA/Training/px1.jpg", 1],
["DatasetA/Training/nx8.jpg", 0],
["DatasetA/Training/nx7.jpg", 0],
["DatasetA/Training/nx52.jpg", 0],
["DatasetA/Training/nx29.jpg", 0],
["DatasetA/Training/nx2.jpg", 0],
["DatasetA/Training/nx25.jpg", 0],
["DatasetA/Training/px13.jpg", 1],
["DatasetA/Training/nx22.jpg", 0],
["DatasetA/Training/nx27.jpg", 0],
["DatasetA/Training/nx9.jpg", 0],
["DatasetA/Testing/nx11.jpg", 0],
["DatasetA/Testing/px30.jpg", 1],
["DatasetA/Testing/nx1.jpg", 0],
["DatasetA/Testing/px45.jpg", 1],
["DatasetA/Training/px28.jpg", 1],
["DatasetA/Training/px42.jpg", 1],
["DatasetA/Training/px21.jpg", 1],
["DatasetA/Training/nx12.jpg", 0],
["DatasetA/Training/nx11.jpg", 0],
["DatasetA/Training/px12.jpg", 1],
["DatasetA/Training/nx13.jpg", 0],
["DatasetA/Training/px43.jpg", 1],
["DatasetA/Testing/px27.jpg", 1],
["DatasetA/Training/px32.jpg", 1],
["DatasetA/Testing/px28.jpg", 1],
["DatasetA/Testing/nx9.jpg", 0],
["DatasetA/Training/px19.jpg", 1],
["DatasetA/Testing/nx4.jpg", 0],
["DatasetA/Training/nx17.jpg", 0],
["DatasetA/Testing/px51.jpg", 1],
["DatasetA/Testing/px29.jpg", 1],
["DatasetA/Training/px18.jpg", 1],
["DatasetA/Testing/nx12.jpg", 0],
["DatasetA/Testing/px34.jpg", 1],
["DatasetA/Training/nx28.jpg", 0],
["DatasetA/Testing/nx7.jpg", 0],
["DatasetA/Training/px46.jpg", 1],
["DatasetA/Training/nx44.jpg", 0],
["DatasetA/Training/nx4.jpg", 0],
["DatasetA/Training/px4.jpg", 1],
["DatasetA/Training/nx42.jpg", 0],
["DatasetA/Training/px17.jpg", 1],
["DatasetA/Training/nx26.jpg", 0],
["DatasetA/Training/px26.jpg", 1],
["DatasetA/Training/px36.jpg", 1],
["DatasetA/Training/px25.jpg", 1],
["DatasetA/Training/px45.jpg", 1],
["DatasetA/Testing/nx3.jpg", 0]
],
"validation": [
["DatasetA/Training/px16.jpg", 1],
["DatasetA/Training/nx20.jpg", 0],
["DatasetA/Testing/px47.jpg", 1],
["DatasetA/Training/px20.jpg", 1],
["DatasetA/Training/px44.jpg", 1],
["DatasetA/Testing/px39.jpg", 1],
["DatasetA/Training/nx6.jpg", 0],
["DatasetA/Training/nx36.jpg", 0],
["DatasetA/Training/nx18.jpg", 0],
["DatasetA/Training/px2.jpg", 1],
["DatasetA/Training/nx50.jpg", 0],
["DatasetA/Training/nx15.jpg", 0],
["DatasetA/Training/px30.jpg", 1],
["DatasetA/Testing/nx14.jpg", 0],
["DatasetA/Testing/nx26.jpg", 0],
["DatasetA/Testing/px49.jpg", 1],
["DatasetA/Training/px48.jpg", 1],
["DatasetA/Training/px51.jpg", 1],
["DatasetA/Training/px23.jpg", 1],
["DatasetA/Testing/px32.jpg", 1],
["DatasetA/Training/nx49.jpg", 0],
["DatasetA/Training/px5.jpg", 1],
["DatasetA/Testing/nx15.jpg", 0],
["DatasetA/Testing/nx2.jpg", 0],
["DatasetA/Testing/nx6.jpg", 0],
["DatasetA/Training/nx24.jpg", 0],
["DatasetA/Testing/nx20.jpg", 0],
["DatasetA/Training/px24.jpg", 1]
],
"test": [
["DatasetA/Training/nx39.jpg", 0],
["DatasetA/Training/nx21.jpg", 0],
["DatasetA/Training/nx33.jpg", 0],
["DatasetA/Training/nx30.jpg", 0],
["DatasetA/Training/px11.jpg", 1],
["DatasetA/Training/px9.jpg", 1],
["DatasetA/Training/px47.jpg", 1],
["DatasetA/Training/px37.jpg", 1],
["DatasetA/Training/nx43.jpg", 0],
["DatasetA/Training/nx3.jpg", 0],
["DatasetA/Training/nx5.jpg", 0],
["DatasetA/Training/px40.jpg", 1],
["DatasetA/Testing/nx10.jpg", 0],
["DatasetA/Testing/px50.jpg", 1],
["DatasetA/Testing/px43.jpg", 1],
["DatasetA/Testing/px46.jpg", 1]
]
}
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...@@ -2,45 +2,6 @@ ...@@ -2,45 +2,6 @@
# #
# SPDX-License-Identifier: GPL-3.0-or-later # SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 0) from .datamodule import DataModule
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set datamodule = DataModule("fold_0.json.bz2")
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_0")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
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{
"train": [
["DatasetA/Training/nx37.jpg", 0],
["DatasetA/Training/nx41.jpg", 0],
["DatasetA/Training/px10.jpg", 1],
["DatasetA/Testing/nx15.jpg", 0],
["DatasetA/Training/px34.jpg", 1],
["DatasetA/Training/nx34.jpg", 0],
["DatasetA/Training/nx36.jpg", 0],
["DatasetA/Training/nx26.jpg", 0],
["DatasetA/Testing/nx12.jpg", 0],
["DatasetA/Testing/nx20.jpg", 0],
["DatasetA/Training/nx46.jpg", 0],
["DatasetA/Training/px19.jpg", 1],
["DatasetA/Testing/nx1.jpg", 0],
["DatasetA/Training/nx29.jpg", 0],
["DatasetA/Training/px45.jpg", 1],
["DatasetA/Training/nx30.jpg", 0],
["DatasetA/Training/px11.jpg", 1],
["DatasetA/Training/px51.jpg", 1],
["DatasetA/Training/px27.jpg", 1],
["DatasetA/Testing/px48.jpg", 1],
["DatasetA/Testing/nx5.jpg", 0],
["DatasetA/Testing/px43.jpg", 1],
["DatasetA/Training/nx43.jpg", 0],
["DatasetA/Training/px17.jpg", 1],
["DatasetA/Training/px31.jpg", 1],
["DatasetA/Training/nx8.jpg", 0],
["DatasetA/Training/px2.jpg", 1],
["DatasetA/Testing/nx8.jpg", 0],
["DatasetA/Training/nx47.jpg", 0],
["DatasetA/Training/nx33.jpg", 0],
["DatasetA/Training/nx18.jpg", 0],
["DatasetA/Training/px39.jpg", 1],
["DatasetA/Training/nx51.jpg", 0],
["DatasetA/Testing/nx9.jpg", 0],
["DatasetA/Training/nx15.jpg", 0],
["DatasetA/Testing/px51.jpg", 1],
["DatasetA/Training/nx17.jpg", 0],
["DatasetA/Training/px6.jpg", 1],
["DatasetA/Training/nx5.jpg", 0],
["DatasetA/Training/px24.jpg", 1],
["DatasetA/Training/px7.jpg", 1],
["DatasetA/Training/px47.jpg", 1],
["DatasetA/Training/nx4.jpg", 0],
["DatasetA/Training/px32.jpg", 1],
["DatasetA/Training/px36.jpg", 1],
["DatasetA/Training/nx13.jpg", 0],
["DatasetA/Training/nx39.jpg", 0],
["DatasetA/Training/px8.jpg", 1],
["DatasetA/Training/nx42.jpg", 0],
["DatasetA/Testing/px46.jpg", 1],
["DatasetA/Training/px18.jpg", 1],
["DatasetA/Testing/px34.jpg", 1],
["DatasetA/Testing/nx22.jpg", 0],
["DatasetA/Training/px48.jpg", 1],
["DatasetA/Training/nx25.jpg", 0],
["DatasetA/Testing/px28.jpg", 1],
["DatasetA/Training/px9.jpg", 1],
["DatasetA/Training/nx45.jpg", 0],
["DatasetA/Testing/nx16.jpg", 0],
["DatasetA/Training/nx31.jpg", 0],
["DatasetA/Testing/nx10.jpg", 0],
["DatasetA/Testing/px29.jpg", 1],
["DatasetA/Training/nx3.jpg", 0],
["DatasetA/Testing/nx26.jpg", 0],
["DatasetA/Testing/px30.jpg", 1],
["DatasetA/Training/px25.jpg", 1],
["DatasetA/Testing/px27.jpg", 1],
["DatasetA/Training/px44.jpg", 1],
["DatasetA/Training/px49.jpg", 1],
["DatasetA/Testing/px37.jpg", 1],
["DatasetA/Training/px38.jpg", 1],
["DatasetA/Training/nx9.jpg", 0],
["DatasetA/Training/px42.jpg", 1],
["DatasetA/Testing/nx23.jpg", 0],
["DatasetA/Training/nx32.jpg", 0],
["DatasetA/Testing/px39.jpg", 1],
["DatasetA/Training/nx12.jpg", 0],
["DatasetA/Training/nx44.jpg", 0],
["DatasetA/Training/px35.jpg", 1],
["DatasetA/Testing/nx17.jpg", 0],
["DatasetA/Testing/nx24.jpg", 0],
["DatasetA/Training/px40.jpg", 1],
["DatasetA/Training/nx11.jpg", 0],
["DatasetA/Testing/nx25.jpg", 0],
["DatasetA/Training/px12.jpg", 1],
["DatasetA/Training/px41.jpg", 1],
["DatasetA/Training/nx27.jpg", 0],
["DatasetA/Training/px14.jpg", 1],
["DatasetA/Training/nx21.jpg", 0],
["DatasetA/Testing/px42.jpg", 1],
["DatasetA/Testing/nx2.jpg", 0],
["DatasetA/Testing/px50.jpg", 1],
["DatasetA/Training/px4.jpg", 1],
["DatasetA/Testing/nx19.jpg", 0],
["DatasetA/Training/px22.jpg", 1],
["DatasetA/Training/nx7.jpg", 0],
["DatasetA/Training/px33.jpg", 1],
["DatasetA/Training/nx14.jpg", 0],
["DatasetA/Training/px37.jpg", 1],
["DatasetA/Testing/nx7.jpg", 0],
["DatasetA/Training/px23.jpg", 1],
["DatasetA/Testing/px33.jpg", 1],
["DatasetA/Testing/nx13.jpg", 0],
["DatasetA/Training/px20.jpg", 1],
["DatasetA/Training/nx35.jpg", 0],
["DatasetA/Testing/px47.jpg", 1],
["DatasetA/Testing/px52.jpg", 1],
["DatasetA/Testing/px35.jpg", 1],
["DatasetA/Training/px21.jpg", 1],
["DatasetA/Testing/px45.jpg", 1],
["DatasetA/Training/nx24.jpg", 0]
],
"validation": [
["DatasetA/Training/px26.jpg", 1],
["DatasetA/Training/px13.jpg", 1],
["DatasetA/Training/px30.jpg", 1],
["DatasetA/Training/px29.jpg", 1],
["DatasetA/Training/px1.jpg", 1],
["DatasetA/Testing/nx14.jpg", 0],
["DatasetA/Testing/px41.jpg", 1],
["DatasetA/Training/nx20.jpg", 0],
["DatasetA/Training/nx16.jpg", 0],
["DatasetA/Training/nx2.jpg", 0],
["DatasetA/Testing/px40.jpg", 1],
["DatasetA/Training/nx49.jpg", 0],
["DatasetA/Training/px16.jpg", 1],
["DatasetA/Training/nx22.jpg", 0],
["DatasetA/Training/nx19.jpg", 0],
["DatasetA/Testing/px49.jpg", 1],
["DatasetA/Testing/nx21.jpg", 0],
["DatasetA/Training/nx6.jpg", 0],
["DatasetA/Training/px3.jpg", 1],
["DatasetA/Testing/px44.jpg", 1],
["DatasetA/Testing/nx11.jpg", 0],
["DatasetA/Testing/nx4.jpg", 0],
["DatasetA/Testing/nx6.jpg", 0],
["DatasetA/Training/px15.jpg", 1],
["DatasetA/Testing/px36.jpg", 1],
["DatasetA/Training/px28.jpg", 1],
["DatasetA/Training/nx10.jpg", 0],
["DatasetA/Training/nx48.jpg", 0]
],
"test": [
["DatasetA/Training/nx52.jpg", 0],
["DatasetA/Training/nx38.jpg", 0],
["DatasetA/Training/nx28.jpg", 0],
["DatasetA/Training/nx1.jpg", 0],
["DatasetA/Training/nx40.jpg", 0],
["DatasetA/Training/px50.jpg", 1],
["DatasetA/Training/px52.jpg", 1],
["DatasetA/Training/px46.jpg", 1],
["DatasetA/Training/nx50.jpg", 0],
["DatasetA/Training/px43.jpg", 1],
["DatasetA/Training/px5.jpg", 1],
["DatasetA/Testing/nx3.jpg", 0],
["DatasetA/Testing/nx18.jpg", 0],
["DatasetA/Testing/px31.jpg", 1],
["DatasetA/Testing/px32.jpg", 1],
["DatasetA/Testing/px38.jpg", 1]
]
}
src/ptbench/data/indian/fold_1.json.bz2 deleted 100644 → 0
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src/ptbench/data/indian/fold_1.py
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...@@ -2,45 +2,6 @@ ...@@ -2,45 +2,6 @@
# #
# SPDX-License-Identifier: GPL-3.0-or-later # SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 1) from .datamodule import DataModule
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set datamodule = DataModule("fold_1.json.bz2")
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_1")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
src/ptbench/data/indian/fold_2.json 0 → 100644
+ 163
− 0
View file @ 819a4380
{
"train": [
["DatasetA/Training/nx7.jpg", 0],
["DatasetA/Testing/nx26.jpg", 0],
["DatasetA/Testing/nx16.jpg", 0],
["DatasetA/Training/nx43.jpg", 0],
["DatasetA/Training/px9.jpg", 1],
["DatasetA/Testing/px27.jpg", 1],
["DatasetA/Testing/px38.jpg", 1],
["DatasetA/Testing/nx5.jpg", 0],
["DatasetA/Testing/nx18.jpg", 0],
["DatasetA/Training/px4.jpg", 1],
["DatasetA/Testing/px28.jpg", 1],
["DatasetA/Training/px36.jpg", 1],
["DatasetA/Training/px8.jpg", 1],
["DatasetA/Training/px30.jpg", 1],
["DatasetA/Training/px17.jpg", 1],
["DatasetA/Training/nx18.jpg", 0],
["DatasetA/Training/px27.jpg", 1],
["DatasetA/Training/px24.jpg", 1],
["DatasetA/Training/nx6.jpg", 0],
["DatasetA/Training/px40.jpg", 1],
["DatasetA/Testing/nx2.jpg", 0],
["DatasetA/Training/nx21.jpg", 0],
["DatasetA/Training/nx12.jpg", 0],
["DatasetA/Testing/nx24.jpg", 0],
["DatasetA/Training/px28.jpg", 1],
["DatasetA/Training/nx33.jpg", 0],
["DatasetA/Training/nx5.jpg", 0],
["DatasetA/Testing/px37.jpg", 1],
["DatasetA/Testing/nx25.jpg", 0],
["DatasetA/Testing/nx12.jpg", 0],
["DatasetA/Training/px47.jpg", 1],
["DatasetA/Training/px11.jpg", 1],
["DatasetA/Testing/px36.jpg", 1],
["DatasetA/Testing/nx13.jpg", 0],
["DatasetA/Training/nx46.jpg", 0],
["DatasetA/Training/px37.jpg", 1],
["DatasetA/Training/px22.jpg", 1],
["DatasetA/Training/nx15.jpg", 0],
["DatasetA/Testing/px44.jpg", 1],
["DatasetA/Testing/px46.jpg", 1],
["DatasetA/Training/nx16.jpg", 0],
["DatasetA/Training/px38.jpg", 1],
["DatasetA/Testing/nx20.jpg", 0],
["DatasetA/Training/nx29.jpg", 0],
["DatasetA/Testing/px30.jpg", 1],
["DatasetA/Training/nx45.jpg", 0],
["DatasetA/Training/px16.jpg", 1],
["DatasetA/Testing/nx9.jpg", 0],
["DatasetA/Training/px15.jpg", 1],
["DatasetA/Testing/nx4.jpg", 0],
["DatasetA/Training/px45.jpg", 1],
["DatasetA/Testing/px47.jpg", 1],
["DatasetA/Testing/px49.jpg", 1],
["DatasetA/Testing/nx1.jpg", 0],
["DatasetA/Training/px21.jpg", 1],
["DatasetA/Training/px7.jpg", 1],
["DatasetA/Training/nx9.jpg", 0],
["DatasetA/Testing/px31.jpg", 1],
["DatasetA/Testing/nx10.jpg", 0],
["DatasetA/Training/px48.jpg", 1],
["DatasetA/Training/px3.jpg", 1],
["DatasetA/Training/nx3.jpg", 0],
["DatasetA/Testing/px48.jpg", 1],
["DatasetA/Training/px51.jpg", 1],
["DatasetA/Testing/nx6.jpg", 0],
["DatasetA/Training/px34.jpg", 1],
["DatasetA/Training/nx42.jpg", 0],
["DatasetA/Testing/px41.jpg", 1],
["DatasetA/Testing/px32.jpg", 1],
["DatasetA/Training/nx52.jpg", 0],
["DatasetA/Testing/nx15.jpg", 0],
["DatasetA/Training/nx17.jpg", 0],
["DatasetA/Testing/px35.jpg", 1],
["DatasetA/Training/px39.jpg", 1],
["DatasetA/Testing/px33.jpg", 1],
["DatasetA/Training/nx41.jpg", 0],
["DatasetA/Training/px49.jpg", 1],
["DatasetA/Training/nx51.jpg", 0],
["DatasetA/Testing/nx22.jpg", 0],
["DatasetA/Training/nx48.jpg", 0],
["DatasetA/Training/px12.jpg", 1],
["DatasetA/Training/nx38.jpg", 0],
["DatasetA/Testing/nx23.jpg", 0],
["DatasetA/Training/nx49.jpg", 0],
["DatasetA/Testing/px50.jpg", 1],
["DatasetA/Training/nx36.jpg", 0],
["DatasetA/Testing/px45.jpg", 1],
["DatasetA/Testing/nx14.jpg", 0],
["DatasetA/Training/nx19.jpg", 0],
["DatasetA/Training/px43.jpg", 1],
["DatasetA/Training/nx10.jpg", 0],
["DatasetA/Training/nx26.jpg", 0],
["DatasetA/Testing/nx3.jpg", 0],
["DatasetA/Training/px10.jpg", 1],
["DatasetA/Training/px50.jpg", 1],
["DatasetA/Training/nx2.jpg", 0],
["DatasetA/Testing/px52.jpg", 1],
["DatasetA/Training/px29.jpg", 1],
["DatasetA/Training/px18.jpg", 1],
["DatasetA/Training/nx35.jpg", 0],
["DatasetA/Training/nx24.jpg", 0],
["DatasetA/Training/px26.jpg", 1],
["DatasetA/Training/nx50.jpg", 0],
["DatasetA/Training/px5.jpg", 1],
["DatasetA/Training/px13.jpg", 1],
["DatasetA/Testing/nx19.jpg", 0],
["DatasetA/Training/nx39.jpg", 0],
["DatasetA/Training/px1.jpg", 1],
["DatasetA/Training/px52.jpg", 1],
["DatasetA/Training/nx20.jpg", 0],
["DatasetA/Training/nx1.jpg", 0]
],
"validation": [
["DatasetA/Testing/px40.jpg", 1],
["DatasetA/Training/px2.jpg", 1],
["DatasetA/Testing/px29.jpg", 1],
["DatasetA/Training/nx8.jpg", 0],
["DatasetA/Training/px23.jpg", 1],
["DatasetA/Testing/nx11.jpg", 0],
["DatasetA/Training/px19.jpg", 1],
["DatasetA/Training/nx14.jpg", 0],
["DatasetA/Training/nx40.jpg", 0],
["DatasetA/Training/nx11.jpg", 0],
["DatasetA/Testing/px39.jpg", 1],
["DatasetA/Training/nx47.jpg", 0],
["DatasetA/Training/nx30.jpg", 0],
["DatasetA/Training/px6.jpg", 1],
["DatasetA/Testing/nx7.jpg", 0],
["DatasetA/Training/px25.jpg", 1],
["DatasetA/Training/nx32.jpg", 0],
["DatasetA/Training/px14.jpg", 1],
["DatasetA/Training/nx27.jpg", 0],
["DatasetA/Training/px46.jpg", 1],
["DatasetA/Testing/px51.jpg", 1],
["DatasetA/Testing/px34.jpg", 1],
["DatasetA/Training/nx13.jpg", 0],
["DatasetA/Training/px32.jpg", 1],
["DatasetA/Training/nx4.jpg", 0],
["DatasetA/Training/nx28.jpg", 0],
["DatasetA/Testing/nx17.jpg", 0],
["DatasetA/Testing/px43.jpg", 1]
],
"test": [
["DatasetA/Training/nx34.jpg", 0],
["DatasetA/Training/nx22.jpg", 0],
["DatasetA/Training/nx37.jpg", 0],
["DatasetA/Training/nx31.jpg", 0],
["DatasetA/Training/nx25.jpg", 0],
["DatasetA/Training/nx44.jpg", 0],
["DatasetA/Training/px35.jpg", 1],
["DatasetA/Training/px20.jpg", 1],
["DatasetA/Training/px31.jpg", 1],
["DatasetA/Training/px33.jpg", 1],
["DatasetA/Training/px44.jpg", 1],
["DatasetA/Training/px42.jpg", 1],
["DatasetA/Training/px41.jpg", 1],
["DatasetA/Testing/nx21.jpg", 0],
["DatasetA/Testing/nx8.jpg", 0],
["DatasetA/Testing/px42.jpg", 1]
]
}
src/ptbench/data/indian/fold_2.json.bz2 deleted 100644 → 0
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src/ptbench/data/indian/fold_2.py
+ 2
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...@@ -2,45 +2,6 @@ ...@@ -2,45 +2,6 @@
# #
# SPDX-License-Identifier: GPL-3.0-or-later # SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 2) from .datamodule import DataModule
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set datamodule = DataModule("fold_2.json.bz2")
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_2")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
src/ptbench/data/indian/fold_3.json 0 → 100644
+ 163
− 0
View file @ 819a4380
{
"train": [
["DatasetA/Training/nx21.jpg", 0],
["DatasetA/Testing/px39.jpg", 1],
["DatasetA/Testing/px45.jpg", 1],
["DatasetA/Testing/px50.jpg", 1],
["DatasetA/Training/nx30.jpg", 0],
["DatasetA/Testing/px33.jpg", 1],
["DatasetA/Testing/nx6.jpg", 0],
["DatasetA/Training/nx11.jpg", 0],
["DatasetA/Training/nx10.jpg", 0],
["DatasetA/Training/nx22.jpg", 0],
["DatasetA/Testing/nx2.jpg", 0],
["DatasetA/Training/nx33.jpg", 0],
["DatasetA/Training/nx40.jpg", 0],
["DatasetA/Training/nx2.jpg", 0],
["DatasetA/Training/nx18.jpg", 0],
["DatasetA/Training/nx47.jpg", 0],
["DatasetA/Training/nx39.jpg", 0],
["DatasetA/Testing/px43.jpg", 1],
["DatasetA/Training/px46.jpg", 1],
["DatasetA/Training/nx44.jpg", 0],
["DatasetA/Training/nx41.jpg", 0],
["DatasetA/Training/px31.jpg", 1],
["DatasetA/Training/px28.jpg", 1],
["DatasetA/Testing/nx9.jpg", 0],
["DatasetA/Training/nx29.jpg", 0],
["DatasetA/Testing/px38.jpg", 1],
["DatasetA/Testing/px32.jpg", 1],
["DatasetA/Testing/px30.jpg", 1],
["DatasetA/Training/nx15.jpg", 0],
["DatasetA/Training/nx37.jpg", 0],
["DatasetA/Training/px10.jpg", 1],
["DatasetA/Training/nx20.jpg", 0],
["DatasetA/Training/px37.jpg", 1],
["DatasetA/Training/nx50.jpg", 0],
["DatasetA/Testing/px42.jpg", 1],
["DatasetA/Training/px11.jpg", 1],
["DatasetA/Training/nx51.jpg", 0],
["DatasetA/Training/px47.jpg", 1],
["DatasetA/Training/nx31.jpg", 0],
["DatasetA/Training/px50.jpg", 1],
["DatasetA/Training/px9.jpg", 1],
["DatasetA/Training/px24.jpg", 1],
["DatasetA/Training/px8.jpg", 1],
["DatasetA/Training/px18.jpg", 1],
["DatasetA/Testing/nx22.jpg", 0],
["DatasetA/Training/px33.jpg", 1],
["DatasetA/Training/nx45.jpg", 0],
["DatasetA/Training/px52.jpg", 1],
["DatasetA/Testing/px34.jpg", 1],
["DatasetA/Testing/nx19.jpg", 0],
["DatasetA/Training/px7.jpg", 1],
["DatasetA/Training/px38.jpg", 1],
["DatasetA/Training/nx32.jpg", 0],
["DatasetA/Training/nx34.jpg", 0],
["DatasetA/Training/px19.jpg", 1],
["DatasetA/Testing/px51.jpg", 1],
["DatasetA/Training/nx46.jpg", 0],
["DatasetA/Training/nx24.jpg", 0],
["DatasetA/Testing/px27.jpg", 1],
["DatasetA/Testing/px48.jpg", 1],
["DatasetA/Testing/px44.jpg", 1],
["DatasetA/Training/px13.jpg", 1],
["DatasetA/Training/nx36.jpg", 0],
["DatasetA/Testing/nx13.jpg", 0],
["DatasetA/Testing/nx7.jpg", 0],
["DatasetA/Training/nx19.jpg", 0],
["DatasetA/Training/px36.jpg", 1],
["DatasetA/Training/nx3.jpg", 0],
["DatasetA/Testing/px28.jpg", 1],
["DatasetA/Training/nx43.jpg", 0],
["DatasetA/Training/px48.jpg", 1],
["DatasetA/Testing/nx4.jpg", 0],
["DatasetA/Testing/px46.jpg", 1],
["DatasetA/Training/nx12.jpg", 0],
["DatasetA/Testing/px47.jpg", 1],
["DatasetA/Training/px5.jpg", 1],
["DatasetA/Training/nx27.jpg", 0],
["DatasetA/Testing/nx20.jpg", 0],
["DatasetA/Training/nx49.jpg", 0],
["DatasetA/Testing/px35.jpg", 1],
["DatasetA/Training/px51.jpg", 1],
["DatasetA/Training/px30.jpg", 1],
["DatasetA/Training/nx25.jpg", 0],
["DatasetA/Training/px32.jpg", 1],
["DatasetA/Training/px23.jpg", 1],
["DatasetA/Testing/px41.jpg", 1],
["DatasetA/Training/px17.jpg", 1],
["DatasetA/Training/px15.jpg", 1],
["DatasetA/Testing/nx18.jpg", 0],
["DatasetA/Training/nx5.jpg", 0],
["DatasetA/Training/px35.jpg", 1],
["DatasetA/Training/nx16.jpg", 0],
["DatasetA/Training/px34.jpg", 1],
["DatasetA/Testing/nx15.jpg", 0],
["DatasetA/Testing/nx10.jpg", 0],
["DatasetA/Testing/nx23.jpg", 0],
["DatasetA/Training/px4.jpg", 1],
["DatasetA/Testing/nx24.jpg", 0],
["DatasetA/Training/nx28.jpg", 0],
["DatasetA/Training/px40.jpg", 1],
["DatasetA/Testing/nx21.jpg", 0],
["DatasetA/Training/px41.jpg", 1],
["DatasetA/Training/px42.jpg", 1],
["DatasetA/Testing/nx25.jpg", 0],
["DatasetA/Training/px45.jpg", 1],
["DatasetA/Testing/nx12.jpg", 0],
["DatasetA/Training/nx42.jpg", 0],
["DatasetA/Training/nx26.jpg", 0],
["DatasetA/Testing/px29.jpg", 1],
["DatasetA/Training/px16.jpg", 1],
["DatasetA/Training/px26.jpg", 1]
],
"validation": [
["DatasetA/Testing/px31.jpg", 1],
["DatasetA/Training/nx38.jpg", 0],
["DatasetA/Training/px44.jpg", 1],
["DatasetA/Testing/nx8.jpg", 0],
["DatasetA/Training/px20.jpg", 1],
["DatasetA/Training/nx7.jpg", 0],
["DatasetA/Training/nx4.jpg", 0],
["DatasetA/Training/px2.jpg", 1],
["DatasetA/Testing/nx5.jpg", 0],
["DatasetA/Testing/nx26.jpg", 0],
["DatasetA/Training/nx48.jpg", 0],
["DatasetA/Training/nx14.jpg", 0],
["DatasetA/Training/nx52.jpg", 0],
["DatasetA/Testing/px52.jpg", 1],
["DatasetA/Training/px3.jpg", 1],
["DatasetA/Training/px14.jpg", 1],
["DatasetA/Training/px39.jpg", 1],
["DatasetA/Training/px1.jpg", 1],
["DatasetA/Training/nx13.jpg", 0],
["DatasetA/Training/px21.jpg", 1],
["DatasetA/Training/nx1.jpg", 0],
["DatasetA/Testing/nx17.jpg", 0],
["DatasetA/Testing/px40.jpg", 1],
["DatasetA/Training/px22.jpg", 1],
["DatasetA/Training/px43.jpg", 1],
["DatasetA/Training/px27.jpg", 1],
["DatasetA/Testing/nx11.jpg", 0],
["DatasetA/Testing/nx3.jpg", 0]
],
"test": [
["DatasetA/Training/nx35.jpg", 0],
["DatasetA/Training/nx17.jpg", 0],
["DatasetA/Training/nx6.jpg", 0],
["DatasetA/Training/nx8.jpg", 0],
["DatasetA/Training/nx9.jpg", 0],
["DatasetA/Training/px29.jpg", 1],
["DatasetA/Training/px49.jpg", 1],
["DatasetA/Training/px25.jpg", 1],
["DatasetA/Training/px12.jpg", 1],
["DatasetA/Training/px6.jpg", 1],
["DatasetA/Testing/nx14.jpg", 0],
["DatasetA/Testing/nx16.jpg", 0],
["DatasetA/Testing/nx1.jpg", 0],
["DatasetA/Testing/px49.jpg", 1],
["DatasetA/Testing/px36.jpg", 1],
["DatasetA/Testing/px37.jpg", 1]
]
}
src/ptbench/data/indian/fold_3.json.bz2 deleted 100644 → 0
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src/ptbench/data/indian/fold_3.py
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...@@ -2,45 +2,6 @@ ...@@ -2,45 +2,6 @@
# #
# SPDX-License-Identifier: GPL-3.0-or-later # SPDX-License-Identifier: GPL-3.0-or-later
"""Indian dataset for TB detection (cross validation fold 3) from .datamodule import DataModule
* Split reference: [INDIAN-2013]_ with 20% of train set for the validation set datamodule = DataModule("fold_3.json.bz2")
* This configuration resolution: 512 x 512 (default)
* See :py:mod:`ptbench.data.indian` for dataset details
"""
from clapper.logging import setup
from .. import return_subsets
from ..base_datamodule import BaseDataModule
from . import _maker
logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
class Fold0Module(BaseDataModule):
def __init__(
self,
train_batch_size=1,
predict_batch_size=1,
drop_incomplete_batch=False,
multiproc_kwargs=None,
):
super().__init__(
train_batch_size=train_batch_size,
predict_batch_size=predict_batch_size,
drop_incomplete_batch=drop_incomplete_batch,
multiproc_kwargs=multiproc_kwargs,
)
def setup(self, stage: str):
self.dataset = _maker("fold_3")
(
self.train_dataset,
self.validation_dataset,
self.extra_validation_datasets,
self.predict_dataset,
) = return_subsets(self.dataset)
datamodule = Fold0Module
src/ptbench/data/indian/fold_4.json 0 → 100644
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{
"train": [
["DatasetA/Training/nx6.jpg", 0],
["DatasetA/Training/px30.jpg", 1],
["DatasetA/Training/nx24.jpg", 0],
["DatasetA/Training/nx13.jpg", 0],
["DatasetA/Testing/px43.jpg", 1],
["DatasetA/Training/px20.jpg", 1],
["DatasetA/Training/nx4.jpg", 0],
["DatasetA/Testing/nx13.jpg", 0],
["DatasetA/Training/px18.jpg", 1],
["DatasetA/Training/nx37.jpg", 0],
["DatasetA/Training/nx22.jpg", 0],
["DatasetA/Training/nx11.jpg", 0],
["DatasetA/Testing/px47.jpg", 1],
["DatasetA/Training/px32.jpg", 1],
["DatasetA/Training/nx49.jpg", 0],
["DatasetA/Training/px8.jpg", 1],
["DatasetA/Training/nx39.jpg", 0],
["DatasetA/Testing/px34.jpg", 1],
["DatasetA/Testing/nx9.jpg", 0],
["DatasetA/Testing/px28.jpg", 1],
["DatasetA/Training/px37.jpg", 1],
["DatasetA/Training/nx52.jpg", 0],
["DatasetA/Training/px9.jpg", 1],
["DatasetA/Testing/nx23.jpg", 0],
["DatasetA/Training/px50.jpg", 1],
["DatasetA/Training/px15.jpg", 1],
["DatasetA/Testing/nx20.jpg", 0],
["DatasetA/Training/nx14.jpg", 0],
["DatasetA/Testing/nx6.jpg", 0],
["DatasetA/Training/px26.jpg", 1],
["DatasetA/Testing/nx8.jpg", 0],
["DatasetA/Testing/nx16.jpg", 0],
["DatasetA/Testing/px35.jpg", 1],
["DatasetA/Testing/px50.jpg", 1],
["DatasetA/Testing/px41.jpg", 1],
["DatasetA/Testing/px45.jpg", 1],
["DatasetA/Training/px33.jpg", 1],
["DatasetA/Testing/px42.jpg", 1],
["DatasetA/Training/nx29.jpg", 0],
["DatasetA/Training/nx10.jpg", 0],
["DatasetA/Testing/nx12.jpg", 0],
["DatasetA/Training/px6.jpg", 1],
["DatasetA/Training/px22.jpg", 1],
["DatasetA/Training/px12.jpg", 1],
["DatasetA/Training/px34.jpg", 1],
["DatasetA/Training/px29.jpg", 1],
["DatasetA/Testing/px36.jpg", 1],
["DatasetA/Training/px14.jpg", 1],
["DatasetA/Testing/nx19.jpg", 0],
["DatasetA/Training/nx48.jpg", 0],
["DatasetA/Training/px19.jpg", 1],
["DatasetA/Testing/px52.jpg", 1],
["DatasetA/Testing/nx7.jpg", 0],
["DatasetA/Training/nx32.jpg", 0],
["DatasetA/Training/px39.jpg", 1],
["DatasetA/Testing/nx21.jpg", 0],
["DatasetA/Training/px25.jpg", 1],
["DatasetA/Testing/nx14.jpg", 0],
["DatasetA/Training/nx46.jpg", 0],
["DatasetA/Testing/px39.jpg", 1],
["DatasetA/Training/px2.jpg", 1],
["DatasetA/Training/nx17.jpg", 0],
["DatasetA/Training/nx1.jpg", 0],
["DatasetA/Training/px36.jpg", 1],
["DatasetA/Training/px40.jpg", 1],
["DatasetA/Training/px31.jpg", 1],
["DatasetA/Testing/nx18.jpg", 0],
["DatasetA/Training/nx50.jpg", 0],
["DatasetA/Training/nx8.jpg", 0],
["DatasetA/Testing/px38.jpg", 1],
["DatasetA/Training/nx3.jpg", 0],
["DatasetA/Training/nx51.jpg", 0],
["DatasetA/Training/nx35.jpg", 0],
["DatasetA/Testing/nx1.jpg", 0],
["DatasetA/Testing/px37.jpg", 1],
["DatasetA/Testing/nx15.jpg", 0],
["DatasetA/Training/nx21.jpg", 0],
["DatasetA/Training/nx45.jpg", 0],
["DatasetA/Training/nx31.jpg", 0],
["DatasetA/Testing/px44.jpg", 1],
["DatasetA/Testing/px48.jpg", 1],
["DatasetA/Testing/px40.jpg", 1],
["DatasetA/Training/nx25.jpg", 0],
["DatasetA/Training/nx40.jpg", 0],
["DatasetA/Training/px1.jpg", 1],
["DatasetA/Training/px5.jpg", 1],
["DatasetA/Training/nx19.jpg", 0],
["DatasetA/Training/nx47.jpg", 0],
["DatasetA/Testing/nx25.jpg", 0],
["DatasetA/Training/nx33.jpg", 0],
["DatasetA/Training/px43.jpg", 1],
["DatasetA/Testing/px30.jpg", 1],
["DatasetA/Training/px46.jpg", 1],
["DatasetA/Testing/nx17.jpg", 0],
["DatasetA/Training/px38.jpg", 1],
["DatasetA/Training/px45.jpg", 1],
["DatasetA/Training/px24.jpg", 1],
["DatasetA/Testing/px32.jpg", 1],
["DatasetA/Training/nx38.jpg", 0],
["DatasetA/Training/px28.jpg", 1],
["DatasetA/Testing/nx11.jpg", 0],
["DatasetA/Training/px47.jpg", 1],
["DatasetA/Training/nx42.jpg", 0],
["DatasetA/Testing/px46.jpg", 1],
["DatasetA/Training/nx12.jpg", 0],
["DatasetA/Training/nx28.jpg", 0],
["DatasetA/Training/px17.jpg", 1],
["DatasetA/Training/nx20.jpg", 0],
["DatasetA/Training/px13.jpg", 1],
["DatasetA/Training/px49.jpg", 1],
["DatasetA/Testing/nx10.jpg", 0]
],
"validation": [
["DatasetA/Testing/nx3.jpg", 0],
["DatasetA/Testing/px31.jpg", 1],
["DatasetA/Training/nx44.jpg", 0],
["DatasetA/Training/px27.jpg", 1],
["DatasetA/Training/px52.jpg", 1],
["DatasetA/Training/nx16.jpg", 0],
["DatasetA/Training/px11.jpg", 1],
["DatasetA/Training/nx26.jpg", 0],
["DatasetA/Training/px7.jpg", 1],
["DatasetA/Training/nx5.jpg", 0],
["DatasetA/Testing/px51.jpg", 1],
["DatasetA/Training/nx34.jpg", 0],
["DatasetA/Training/nx43.jpg", 0],
["DatasetA/Training/px41.jpg", 1],
["DatasetA/Training/nx27.jpg", 0],
["DatasetA/Training/px44.jpg", 1],
["DatasetA/Training/nx30.jpg", 0],
["DatasetA/Training/nx9.jpg", 0],
["DatasetA/Training/nx7.jpg", 0],
["DatasetA/Training/px42.jpg", 1],
["DatasetA/Testing/nx2.jpg", 0],
["DatasetA/Testing/px27.jpg", 1],
["DatasetA/Testing/nx26.jpg", 0],
["DatasetA/Training/px35.jpg", 1],
["DatasetA/Training/nx2.jpg", 0],
["DatasetA/Training/px48.jpg", 1],
["DatasetA/Training/px23.jpg", 1],
["DatasetA/Testing/px49.jpg", 1]
],
"test": [
["DatasetA/Training/nx36.jpg", 0],
["DatasetA/Training/nx15.jpg", 0],
["DatasetA/Training/nx18.jpg", 0],
["DatasetA/Training/nx41.jpg", 0],
["DatasetA/Training/px51.jpg", 1],
["DatasetA/Training/px10.jpg", 1],
["DatasetA/Training/px16.jpg", 1],
["DatasetA/Training/px21.jpg", 1],
["DatasetA/Training/px3.jpg", 1],
["DatasetA/Training/px4.jpg", 1],
["DatasetA/Testing/nx22.jpg", 0],
["DatasetA/Testing/nx24.jpg", 0],
["DatasetA/Testing/nx5.jpg", 0],
["DatasetA/Testing/nx4.jpg", 0],
["DatasetA/Testing/px29.jpg", 1],
["DatasetA/Testing/px33.jpg", 1]
]
}
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