From b5d3ed3d260f817e00c3f9cbdc317dfe20025b81 Mon Sep 17 00:00:00 2001
From: dcarron <daniel.carron@idiap.ch>
Date: Thu, 6 Jun 2024 10:07:33 +0200
Subject: [PATCH] [segmentation] Add drhagis database
---
.gitattributes | 1 +
pyproject.toml | 3 +
.../config/data/drhagis/__init__.py | 0
.../config/data/drhagis/datamodule.py | 103 +++++++++
.../config/data/drhagis/default.json | 201 ++++++++++++++++++
.../config/data/drhagis/default.py | 11 +
.../histograms_lwnet_drhagis_default.json | 16 ++
.../raw_data/histograms_drhagis_default.json | 16 ++
.../libs/segmentation/tests/test_drhagis.py | 132 ++++++++++++
9 files changed, 483 insertions(+)
create mode 100644 .gitattributes
create mode 100644 src/mednet/libs/segmentation/config/data/drhagis/__init__.py
create mode 100644 src/mednet/libs/segmentation/config/data/drhagis/datamodule.py
create mode 100644 src/mednet/libs/segmentation/config/data/drhagis/default.json
create mode 100644 src/mednet/libs/segmentation/config/data/drhagis/default.py
create mode 100644 src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_drhagis_default.json
create mode 100644 src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_drhagis_default.json
create mode 100644 src/mednet/libs/segmentation/tests/test_drhagis.py
diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 00000000..5bf898cb
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1 @@
+src/mednet/libs/segmentation/config/data/cxr8/default.json filter=lfs diff=lfs merge=lfs -text
diff --git a/pyproject.toml b/pyproject.toml
index 910ff540..73ae90e9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -430,6 +430,9 @@ chasedb1-2nd = "mednet.libs.segmentation.config.data.chasedb1.second_annotator"
# cxr8 - cxr
cxr8 = "mednet.libs.segmentation.config.data.cxr8.default"
+# drhagis dataset - retinography
+drhagis = "mednet.libs.segmentation.config.data.drhagis.default"
+
# drive dataset - retinography
drive = "mednet.libs.segmentation.config.data.drive.default"
diff --git a/src/mednet/libs/segmentation/config/data/drhagis/__init__.py b/src/mednet/libs/segmentation/config/data/drhagis/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/src/mednet/libs/segmentation/config/data/drhagis/datamodule.py b/src/mednet/libs/segmentation/config/data/drhagis/datamodule.py
new file mode 100644
index 00000000..519e635f
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/drhagis/datamodule.py
@@ -0,0 +1,103 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""DRHAGIS dataset for Vessel Segmentation."""
+
+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.data.typing import Sample
+from mednet.libs.common.models.transforms import crop_image_to_mask
+from mednet.libs.segmentation.data.typing import (
+ SegmentationRawDataLoader as _SegmentationRawDataLoader,
+)
+from torchvision import tv_tensors
+from torchvision.transforms.functional import to_tensor
+
+from ....utils.rc import load_rc
+
+CONFIGURATION_KEY_DATADIR = "datadir." + (__name__.rsplit(".", 2)[-2])
+"""Key to search for in the configuration file for the root directory of this
+database."""
+
+
+class SegmentationRawDataLoader(_SegmentationRawDataLoader):
+ """A specialized raw-data-loader for the Drive dataset."""
+
+ datadir: pathlib.Path
+ """This variable contains the base directory where the database raw data is
+ stored."""
+
+ def __init__(self):
+ self.datadir = pathlib.Path(
+ load_rc().get(CONFIGURATION_KEY_DATADIR, os.path.realpath(os.curdir))
+ )
+
+ def sample(self, sample: tuple[str, str, str]) -> Sample:
+ """Load a single image sample from the disk.
+
+ Parameters
+ ----------
+ sample
+ A tuple containing path suffixes to the sample image, target, and mask
+ to be loaded, within the dataset root folder.
+
+ Returns
+ -------
+ The sample representation.
+ """
+
+ image = to_tensor(PIL.Image.open(self.datadir / sample[0]).convert(mode="RGB"))
+ target = to_tensor(
+ PIL.Image.open(self.datadir / sample[1]).convert(mode="1", dither=None)
+ )
+ mask = to_tensor(
+ PIL.Image.open(self.datadir / sample[2]).convert(mode="1", dither=None)
+ )
+
+ tensor = tv_tensors.Image(crop_image_to_mask(image, mask))
+ target = tv_tensors.Image(crop_image_to_mask(target, mask))
+ mask = tv_tensors.Mask(crop_image_to_mask(mask, mask))
+
+ return tensor, dict(target=target, mask=mask, name=sample[0]) # type: ignore[arg-type]
+
+
+class DataModule(CachingDataModule):
+ """DRHAGIS dataset for Vessel Segmentation.
+
+ The DR HAGIS database has been created to aid the development of vessel extraction algorithms
+ suitable for retinal screening programmes. Researchers are encouraged to test their
+ segmentation algorithms using this database.
+
+ It should be noted that image 24 and 32 are identical, as this fundus image was obtained
+ from a patient exhibiting both diabetic retinopathy and age-related macular degeneration.
+
+ The images resolutions (height x width) are:
+ - 4752x3168 or
+ - 3456x2304 or
+ - 3126x2136 or
+ - 2896x1944 or
+ - 2816x1880 or
+
+ * Protocol ``default``:
+
+ * Training samples: 19 (including labels and masks)
+ * Test samples: 20 (including labels and masks)
+
+ Parameters
+ ----------
+ split_filename
+ Name of the .json file containing the split to load.
+ """
+
+ def __init__(self, split_filename: str):
+ assert __package__ is not None
+ super().__init__(
+ database_split=make_split(__package__, split_filename),
+ raw_data_loader=SegmentationRawDataLoader(),
+ database_name=__package__.rsplit(".", 1)[1],
+ split_name=pathlib.Path(split_filename).stem,
+ )
diff --git a/src/mednet/libs/segmentation/config/data/drhagis/default.json b/src/mednet/libs/segmentation/config/data/drhagis/default.json
new file mode 100644
index 00000000..a77353e8
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/drhagis/default.json
@@ -0,0 +1,201 @@
+{
+ "train": [
+ [
+ "Fundus_Images/1.jpg",
+ "Manual_Segmentations/1_manual_orig.png",
+ "Mask_images/1_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/2.jpg",
+ "Manual_Segmentations/2_manual_orig.png",
+ "Mask_images/2_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/3.jpg",
+ "Manual_Segmentations/3_manual_orig.png",
+ "Mask_images/3_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/4.jpg",
+ "Manual_Segmentations/4_manual_orig.png",
+ "Mask_images/4_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/5.jpg",
+ "Manual_Segmentations/5_manual_orig.png",
+ "Mask_images/5_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/11.jpg",
+ "Manual_Segmentations/11_manual_orig.png",
+ "Mask_images/11_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/12.jpg",
+ "Manual_Segmentations/12_manual_orig.png",
+ "Mask_images/12_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/13.jpg",
+ "Manual_Segmentations/13_manual_orig.png",
+ "Mask_images/13_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/14.jpg",
+ "Manual_Segmentations/14_manual_orig.png",
+ "Mask_images/14_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/15.jpg",
+ "Manual_Segmentations/15_manual_orig.png",
+ "Mask_images/15_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/21.jpg",
+ "Manual_Segmentations/21_manual_orig.png",
+ "Mask_images/21_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/22.jpg",
+ "Manual_Segmentations/22_manual_orig.png",
+ "Mask_images/22_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/23.jpg",
+ "Manual_Segmentations/23_manual_orig.png",
+ "Mask_images/23_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/24.jpg",
+ "Manual_Segmentations/24_manual_orig.png",
+ "Mask_images/24_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/25.jpg",
+ "Manual_Segmentations/25_manual_orig.png",
+ "Mask_images/25_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/31.jpg",
+ "Manual_Segmentations/31_manual_orig.png",
+ "Mask_images/31_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/33.jpg",
+ "Manual_Segmentations/33_manual_orig.png",
+ "Mask_images/33_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/34.jpg",
+ "Manual_Segmentations/34_manual_orig.png",
+ "Mask_images/34_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/35.jpg",
+ "Manual_Segmentations/35_manual_orig.png",
+ "Mask_images/35_mask_orig.png"
+ ]
+ ],
+ "test": [
+ [
+ "Fundus_Images/6.jpg",
+ "Manual_Segmentations/6_manual_orig.png",
+ "Mask_images/6_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/7.jpg",
+ "Manual_Segmentations/7_manual_orig.png",
+ "Mask_images/7_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/8.jpg",
+ "Manual_Segmentations/8_manual_orig.png",
+ "Mask_images/8_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/9.jpg",
+ "Manual_Segmentations/9_manual_orig.png",
+ "Mask_images/9_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/10.jpg",
+ "Manual_Segmentations/10_manual_orig.png",
+ "Mask_images/10_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/16.jpg",
+ "Manual_Segmentations/16_manual_orig.png",
+ "Mask_images/16_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/17.jpg",
+ "Manual_Segmentations/17_manual_orig.png",
+ "Mask_images/17_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/18.jpg",
+ "Manual_Segmentations/18_manual_orig.png",
+ "Mask_images/18_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/19.jpg",
+ "Manual_Segmentations/19_manual_orig.png",
+ "Mask_images/19_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/20.jpg",
+ "Manual_Segmentations/20_manual_orig.png",
+ "Mask_images/20_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/26.jpg",
+ "Manual_Segmentations/26_manual_orig.png",
+ "Mask_images/26_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/27.jpg",
+ "Manual_Segmentations/27_manual_orig.png",
+ "Mask_images/27_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/28.jpg",
+ "Manual_Segmentations/28_manual_orig.png",
+ "Mask_images/28_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/29.jpg",
+ "Manual_Segmentations/29_manual_orig.png",
+ "Mask_images/29_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/30.jpg",
+ "Manual_Segmentations/30_manual_orig.png",
+ "Mask_images/30_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/36.jpg",
+ "Manual_Segmentations/36_manual_orig.png",
+ "Mask_images/36_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/37.jpg",
+ "Manual_Segmentations/37_manual_orig.png",
+ "Mask_images/37_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/38.jpg",
+ "Manual_Segmentations/38_manual_orig.png",
+ "Mask_images/38_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/39.jpg",
+ "Manual_Segmentations/39_manual_orig.png",
+ "Mask_images/39_mask_orig.png"
+ ],
+ [
+ "Fundus_Images/40.jpg",
+ "Manual_Segmentations/40_manual_orig.png",
+ "Mask_images/40_mask_orig.png"
+ ]
+ ]
+}
diff --git a/src/mednet/libs/segmentation/config/data/drhagis/default.py b/src/mednet/libs/segmentation/config/data/drhagis/default.py
new file mode 100644
index 00000000..c0c5ad84
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/drhagis/default.py
@@ -0,0 +1,11 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""DRHAGIS dataset for Vessel Segmentation (default protocol).
+
+* This configuration resolution: 1760 x 1760 (Resizing)
+"""
+
+from mednet.libs.segmentation.config.data.drhagis.datamodule import DataModule
+
+datamodule = DataModule("default.json")
diff --git a/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_drhagis_default.json b/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_drhagis_default.json
new file mode 100644
index 00000000..2007d427
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_drhagis_default.json
@@ -0,0 +1,16 @@
+{
+ "train": [
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+}
diff --git a/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_drhagis_default.json b/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_drhagis_default.json
new file mode 100644
index 00000000..68f9e4eb
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_drhagis_default.json
@@ -0,0 +1,16 @@
+{
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+ ]
+}
diff --git a/src/mednet/libs/segmentation/tests/test_drhagis.py b/src/mednet/libs/segmentation/tests/test_drhagis.py
new file mode 100644
index 00000000..48001248
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/test_drhagis.py
@@ -0,0 +1,132 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""Tests for drhagis dataset."""
+
+import importlib
+
+import pytest
+from click.testing import CliRunner
+
+
+def id_function(val):
+ if isinstance(val, dict):
+ return str(val)
+ return repr(val)
+
+
+@pytest.mark.parametrize(
+ "split,lengths",
+ [
+ ("default", dict(train=19, test=20)),
+ ],
+ ids=id_function, # just changes how pytest prints it
+)
+def test_protocol_consistency(
+ database_checkers,
+ split: str,
+ lengths: dict[str, int],
+):
+ from mednet.libs.common.data.split import make_split
+
+ database_checkers.check_split(
+ make_split("mednet.libs.segmentation.config.data.drhagis", f"{split}.json"),
+ lengths=lengths,
+ )
+
+
+@pytest.mark.skip_if_rc_var_not_set("datadir.drhagis")
+def test_database_check():
+ from mednet.libs.segmentation.scripts.database import check
+
+ runner = CliRunner()
+ result = runner.invoke(check, ["drhagis"])
+ assert (
+ result.exit_code == 0
+ ), f"Exit code {result.exit_code} != 0 -- Output:\n{result.output}"
+
+
+@pytest.mark.skip_if_rc_var_not_set("datadir.drhagis")
+@pytest.mark.parametrize(
+ "dataset",
+ [
+ "train",
+ "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.drhagis",
+ ).datamodule
+
+ datamodule.model_transforms = [] # should be done before setup()
+ datamodule.setup("predict") # sets up all datasets
+
+ loader = datamodule.predict_dataloader()[dataset]
+
+ limit = 3 # limit load checking
+ for batch in loader:
+ if limit == 0:
+ break
+ database_checkers.check_loaded_batch(
+ batch,
+ batch_size=1,
+ color_planes=3,
+ expected_num_targets=1,
+ )
+ limit -= 1
+
+
+@pytest.mark.skip_if_rc_var_not_set("datadir.drhagis")
+def test_raw_transforms_image_quality(database_checkers, datadir):
+ reference_histogram_file = str(
+ datadir / "histograms/raw_data/histograms_drhagis_default.json",
+ )
+
+ datamodule = importlib.import_module(
+ ".default",
+ "mednet.libs.segmentation.config.data.drhagis",
+ ).datamodule
+
+ datamodule.model_transforms = []
+ datamodule.setup("predict")
+
+ database_checkers.check_image_quality(datamodule, reference_histogram_file)
+
+
+@pytest.mark.skip_if_rc_var_not_set("datadir.drhagis")
+@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}_drhagis_default.json",
+ )
+
+ datamodule = importlib.import_module(
+ ".default",
+ "mednet.libs.segmentation.config.data.drhagis",
+ ).datamodule
+
+ model = importlib.import_module(
+ f".{model_name}",
+ "mednet.libs.segmentation.config.models",
+ ).model
+
+ datamodule.model_transforms = model.model_transforms
+ datamodule.setup("predict")
+
+ database_checkers.check_image_quality(
+ datamodule,
+ reference_histogram_file,
+ compare_type="statistical",
+ pearson_coeff_threshold=0.005,
+ )
--
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