From c68b73d064e3a8c54bef376868daad32b54bdabe Mon Sep 17 00:00:00 2001
From: dcarron <daniel.carron@idiap.ch>
Date: Tue, 28 May 2024 11:34:12 +0200
Subject: [PATCH] [segmentation] Add chasedb1 database
---
pyproject.toml | 8 +-
.../config/data/chasedb1/__init__.py | 0
.../config/data/chasedb1/datamodule.py | 135 ++++++++++++++++
.../config/data/chasedb1/first-annotator.json | 146 ++++++++++++++++++
.../config/data/chasedb1/first_annotator.py | 8 +
.../config/data/chasedb1/masks/Image_01L.png | Bin 0 -> 1955 bytes
.../config/data/chasedb1/masks/Image_01R.png | Bin 0 -> 1936 bytes
.../config/data/chasedb1/masks/Image_02L.png | Bin 0 -> 1942 bytes
.../config/data/chasedb1/masks/Image_02R.png | Bin 0 -> 1930 bytes
.../config/data/chasedb1/masks/Image_03L.png | Bin 0 -> 1934 bytes
.../config/data/chasedb1/masks/Image_03R.png | Bin 0 -> 1955 bytes
.../config/data/chasedb1/masks/Image_04L.png | Bin 0 -> 1925 bytes
.../config/data/chasedb1/masks/Image_04R.png | Bin 0 -> 1938 bytes
.../config/data/chasedb1/masks/Image_05L.png | Bin 0 -> 1919 bytes
.../config/data/chasedb1/masks/Image_05R.png | Bin 0 -> 1954 bytes
.../config/data/chasedb1/masks/Image_06L.png | Bin 0 -> 1918 bytes
.../config/data/chasedb1/masks/Image_06R.png | Bin 0 -> 1916 bytes
.../config/data/chasedb1/masks/Image_07L.png | Bin 0 -> 1924 bytes
.../config/data/chasedb1/masks/Image_07R.png | Bin 0 -> 1923 bytes
.../config/data/chasedb1/masks/Image_08L.png | Bin 0 -> 1930 bytes
.../config/data/chasedb1/masks/Image_08R.png | Bin 0 -> 1919 bytes
.../config/data/chasedb1/masks/Image_09L.png | Bin 0 -> 1915 bytes
.../config/data/chasedb1/masks/Image_09R.png | Bin 0 -> 1941 bytes
.../config/data/chasedb1/masks/Image_10L.png | Bin 0 -> 1921 bytes
.../config/data/chasedb1/masks/Image_10R.png | Bin 0 -> 1919 bytes
.../config/data/chasedb1/masks/Image_11L.png | Bin 0 -> 1955 bytes
.../config/data/chasedb1/masks/Image_11R.png | Bin 0 -> 1943 bytes
.../config/data/chasedb1/masks/Image_12L.png | Bin 0 -> 1960 bytes
.../config/data/chasedb1/masks/Image_12R.png | Bin 0 -> 1932 bytes
.../config/data/chasedb1/masks/Image_13L.png | Bin 0 -> 1926 bytes
.../config/data/chasedb1/masks/Image_13R.png | Bin 0 -> 1915 bytes
.../config/data/chasedb1/masks/Image_14L.png | Bin 0 -> 1952 bytes
.../config/data/chasedb1/masks/Image_14R.png | Bin 0 -> 1891 bytes
.../data/chasedb1/second-annotator.json | 146 ++++++++++++++++++
.../config/data/chasedb1/second_annotator.py | 8 +
...ograms_lwnet_chasedb1_first_annotator.json | 16 ++
.../histograms_chasedb1_first_annotator.json | 16 ++
.../libs/segmentation/tests/test_chasedb1.py | 138 +++++++++++++++++
38 files changed, 620 insertions(+), 1 deletion(-)
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/__init__.py
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/first-annotator.json
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/first_annotator.py
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_01L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_01R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_02L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_02R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_03L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_03R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_04L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_04R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_05L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_05R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_06L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_06R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_07L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_07R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_08L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_08R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_09L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_09R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_10L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_10R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_11L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_11R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_12L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_12R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_13L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_13R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_14L.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/masks/Image_14R.png
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/second-annotator.json
create mode 100644 src/mednet/libs/segmentation/config/data/chasedb1/second_annotator.py
create mode 100644 src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json
create mode 100644 src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_chasedb1_first_annotator.json
create mode 100644 src/mednet/libs/segmentation/tests/test_chasedb1.py
diff --git a/pyproject.toml b/pyproject.toml
index 0be3495e..2ec302d6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -423,8 +423,14 @@ visceral = "mednet.config.data.visceral.default"
lwnet = "mednet.libs.segmentation.config.models.lwnet"
-# drive dataset - retinal vessel segmentation
+# chase-db1 - retinography
+chasedb1 = "mednet.libs.segmentation.config.data.chasedb1.first_annotator"
+chasedb1-2nd = "mednet.libs.segmentation.config.data.chasedb1.second_annotator"
+
+# drive dataset - retinography
drive = "mednet.libs.segmentation.config.data.drive.default"
+
+# stare dataset - retinography
stare = "mednet.libs.segmentation.config.data.stare.ah"
stare-2nd = "mednet.libs.segmentation.config.data.stare.vk"
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/__init__.py b/src/mednet/libs/segmentation/config/data/chasedb1/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py b/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py
new file mode 100644
index 00000000..f8dfa0bc
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py
@@ -0,0 +1,135 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""CHASE-DB1 dataset for Vessel Segmentation."""
+
+import importlib.resources
+import os
+from pathlib import Path
+
+import PIL.Image
+import pkg_resources
+from mednet.libs.common.data.datamodule import CachingDataModule
+from mednet.libs.common.data.split import JSONDatabaseSplit
+from mednet.libs.common.data.typing import DatabaseSplit, Sample
+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 Chase-db1 dataset."""
+
+ datadir: str
+ """This variable contains the base directory where the database raw data is
+ stored."""
+
+ def __init__(self):
+ self.datadir = load_rc().get(
+ CONFIGURATION_KEY_DATADIR, os.path.realpath(os.curdir)
+ )
+
+ self._pkg_path = pkg_resources.resource_filename(__name__, "masks")
+
+ 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 = PIL.Image.open(Path(self.datadir) / str(sample[0])).convert(
+ mode="RGB"
+ )
+ tensor = tv_tensors.Image(to_tensor(image))
+ target = tv_tensors.Image(
+ to_tensor(
+ PIL.Image.open(Path(self.datadir) / str(sample[1])).convert(
+ mode="1", dither=None
+ )
+ )
+ )
+ mask = tv_tensors.Mask(
+ to_tensor(
+ PIL.Image.open(Path(self._pkg_path) / str(sample[2])).convert(
+ mode="1", dither=None
+ )
+ )
+ )
+
+ return tensor, dict(target=target, mask=mask, name=sample[0]) # type: ignore[arg-type]
+
+
+def make_split(basename: str) -> DatabaseSplit:
+ """Return a database split for the Chase-db1 database.
+
+ Parameters
+ ----------
+ basename
+ Name of the .json file containing the split to load.
+
+ Returns
+ -------
+ An instance of DatabaseSplit.
+ """
+
+ return JSONDatabaseSplit(
+ importlib.resources.files(__name__.rsplit(".", 1)[0]).joinpath(basename)
+ )
+
+
+class DataModule(CachingDataModule):
+ """CHASE-DB1 dataset for Vessel Segmentation.
+
+ The CHASE_DB1 is a retinal vessel reference dataset acquired from multiethnic
+ school children. This database is a part of the Child Heart and Health Study in
+ England (CHASE), a cardiovascular health survey in 200 primary schools in
+ London, Birmingham, and Leicester. The ocular imaging was carried out in
+ 46 schools and demonstrated associations between retinal vessel tortuosity and
+ early risk factors for cardiovascular disease in over 1000 British primary
+ school children of different ethnic origin. The retinal images of both of the
+ eyes of each child were recorded with a hand-held Nidek NM-200-D fundus camera.
+ The images were captured at 30 degrees FOV camera. The dataset of images are
+ characterized by having nonuniform back-ground illumination, poor contrast of
+ blood vessels as compared with the background and wider arteriolars that have a
+ bright strip running down the centre known as the central vessel reflex.
+
+ * Reference: [CHASEDB1-2012]_
+ * Original resolution (height x width): 960 x 999
+ * Split reference: [CHASEDB1-2012]_
+ * Protocol ``first-annotator``:
+
+ * Training samples: 8 (including labels from annotator "1stHO")
+ * Test samples: 20 (including labels from annotator "1stHO")
+
+ * Protocol ``second-annotator``:
+
+ * Training samples: 8 (including labels from annotator "2ndHO")
+ * Test samples: 20 (including labels from annotator "2ndHO")
+
+ Parameters
+ ----------
+ split_filename
+ Name of the .json file containing the split to load.
+ """
+
+ def __init__(self, split_filename: str):
+ super().__init__(
+ database_split=make_split(split_filename),
+ raw_data_loader=SegmentationRawDataLoader(),
+ )
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/first-annotator.json b/src/mednet/libs/segmentation/config/data/chasedb1/first-annotator.json
new file mode 100644
index 00000000..52335077
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/first-annotator.json
@@ -0,0 +1,146 @@
+{
+ "train": [
+ [
+ "Image_11L.jpg",
+ "Image_11L_1stHO.png",
+ "Image_11L.png"
+ ],
+ [
+ "Image_11R.jpg",
+ "Image_11R_1stHO.png",
+ "Image_11R.png"
+ ],
+ [
+ "Image_12L.jpg",
+ "Image_12L_1stHO.png",
+ "Image_12L.png"
+ ],
+ [
+ "Image_12R.jpg",
+ "Image_12R_1stHO.png",
+ "Image_12R.png"
+ ],
+ [
+ "Image_13L.jpg",
+ "Image_13L_1stHO.png",
+ "Image_13L.png"
+ ],
+ [
+ "Image_13R.jpg",
+ "Image_13R_1stHO.png",
+ "Image_13R.png"
+ ],
+ [
+ "Image_14L.jpg",
+ "Image_14L_1stHO.png",
+ "Image_14L.png"
+ ],
+ [
+ "Image_14R.jpg",
+ "Image_14R_1stHO.png",
+ "Image_14R.png"
+ ]
+ ],
+ "test": [
+ [
+ "Image_01L.jpg",
+ "Image_01L_1stHO.png",
+ "Image_01L.png"
+ ],
+ [
+ "Image_01R.jpg",
+ "Image_01R_1stHO.png",
+ "Image_01R.png"
+ ],
+ [
+ "Image_02L.jpg",
+ "Image_02L_1stHO.png",
+ "Image_02L.png"
+ ],
+ [
+ "Image_02R.jpg",
+ "Image_02R_1stHO.png",
+ "Image_02R.png"
+ ],
+ [
+ "Image_03L.jpg",
+ "Image_03L_1stHO.png",
+ "Image_03L.png"
+ ],
+ [
+ "Image_03R.jpg",
+ "Image_03R_1stHO.png",
+ "Image_03R.png"
+ ],
+ [
+ "Image_04L.jpg",
+ "Image_04L_1stHO.png",
+ "Image_04L.png"
+ ],
+ [
+ "Image_04R.jpg",
+ "Image_04R_1stHO.png",
+ "Image_04R.png"
+ ],
+ [
+ "Image_05L.jpg",
+ "Image_05L_1stHO.png",
+ "Image_05L.png"
+ ],
+ [
+ "Image_05R.jpg",
+ "Image_05R_1stHO.png",
+ "Image_05R.png"
+ ],
+ [
+ "Image_06L.jpg",
+ "Image_06L_1stHO.png",
+ "Image_06L.png"
+ ],
+ [
+ "Image_06R.jpg",
+ "Image_06R_1stHO.png",
+ "Image_06R.png"
+ ],
+ [
+ "Image_07L.jpg",
+ "Image_07L_1stHO.png",
+ "Image_07L.png"
+ ],
+ [
+ "Image_07R.jpg",
+ "Image_07R_1stHO.png",
+ "Image_07R.png"
+ ],
+ [
+ "Image_08L.jpg",
+ "Image_08L_1stHO.png",
+ "Image_08L.png"
+ ],
+ [
+ "Image_08R.jpg",
+ "Image_08R_1stHO.png",
+ "Image_08R.png"
+ ],
+ [
+ "Image_09L.jpg",
+ "Image_09L_1stHO.png",
+ "Image_09L.png"
+ ],
+ [
+ "Image_09R.jpg",
+ "Image_09R_1stHO.png",
+ "Image_09R.png"
+ ],
+ [
+ "Image_10L.jpg",
+ "Image_10L_1stHO.png",
+ "Image_10L.png"
+ ],
+ [
+ "Image_10R.jpg",
+ "Image_10R_1stHO.png",
+ "Image_10R.png"
+ ]
+ ]
+}
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/first_annotator.py b/src/mednet/libs/segmentation/config/data/chasedb1/first_annotator.py
new file mode 100644
index 00000000..eae56453
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/first_annotator.py
@@ -0,0 +1,8 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""CHASE-DB1 dataset for Vessel Segmentation."""
+
+from mednet.libs.segmentation.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/libs/segmentation/config/data/chasedb1/masks/Image_01L.png
new file mode 100644
index 0000000000000000000000000000000000000000..121a1904a1c48c6c4d10230bb823d84e7d26190d
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diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/second-annotator.json b/src/mednet/libs/segmentation/config/data/chasedb1/second-annotator.json
new file mode 100644
index 00000000..9f2da7f2
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/second-annotator.json
@@ -0,0 +1,146 @@
+{
+ "train": [
+ [
+ "Image_11L.jpg",
+ "Image_11L_2ndHO.png",
+ "Image_11L.png"
+ ],
+ [
+ "Image_11R.jpg",
+ "Image_11R_2ndHO.png",
+ "Image_11R.png"
+ ],
+ [
+ "Image_12L.jpg",
+ "Image_12L_2ndHO.png",
+ "Image_12L.png"
+ ],
+ [
+ "Image_12R.jpg",
+ "Image_12R_2ndHO.png",
+ "Image_12R.png"
+ ],
+ [
+ "Image_13L.jpg",
+ "Image_13L_2ndHO.png",
+ "Image_13L.png"
+ ],
+ [
+ "Image_13R.jpg",
+ "Image_13R_2ndHO.png",
+ "Image_13R.png"
+ ],
+ [
+ "Image_14L.jpg",
+ "Image_14L_2ndHO.png",
+ "Image_14L.png"
+ ],
+ [
+ "Image_14R.jpg",
+ "Image_14R_2ndHO.png",
+ "Image_14R.png"
+ ]
+ ],
+ "test": [
+ [
+ "Image_01L.jpg",
+ "Image_01L_2ndHO.png",
+ "Image_01L.png"
+ ],
+ [
+ "Image_01R.jpg",
+ "Image_01R_2ndHO.png",
+ "Image_01R.png"
+ ],
+ [
+ "Image_02L.jpg",
+ "Image_02L_2ndHO.png",
+ "Image_02L.png"
+ ],
+ [
+ "Image_02R.jpg",
+ "Image_02R_2ndHO.png",
+ "Image_02R.png"
+ ],
+ [
+ "Image_03L.jpg",
+ "Image_03L_2ndHO.png",
+ "Image_03L.png"
+ ],
+ [
+ "Image_03R.jpg",
+ "Image_03R_2ndHO.png",
+ "Image_03R.png"
+ ],
+ [
+ "Image_04L.jpg",
+ "Image_04L_2ndHO.png",
+ "Image_04L.png"
+ ],
+ [
+ "Image_04R.jpg",
+ "Image_04R_2ndHO.png",
+ "Image_04R.png"
+ ],
+ [
+ "Image_05L.jpg",
+ "Image_05L_2ndHO.png",
+ "Image_05L.png"
+ ],
+ [
+ "Image_05R.jpg",
+ "Image_05R_2ndHO.png",
+ "Image_05R.png"
+ ],
+ [
+ "Image_06L.jpg",
+ "Image_06L_2ndHO.png",
+ "Image_06L.png"
+ ],
+ [
+ "Image_06R.jpg",
+ "Image_06R_2ndHO.png",
+ "Image_06R.png"
+ ],
+ [
+ "Image_07L.jpg",
+ "Image_07L_2ndHO.png",
+ "Image_07L.png"
+ ],
+ [
+ "Image_07R.jpg",
+ "Image_07R_2ndHO.png",
+ "Image_07R.png"
+ ],
+ [
+ "Image_08L.jpg",
+ "Image_08L_2ndHO.png",
+ "Image_08L.png"
+ ],
+ [
+ "Image_08R.jpg",
+ "Image_08R_2ndHO.png",
+ "Image_08R.png"
+ ],
+ [
+ "Image_09L.jpg",
+ "Image_09L_2ndHO.png",
+ "Image_09L.png"
+ ],
+ [
+ "Image_09R.jpg",
+ "Image_09R_2ndHO.png",
+ "Image_09R.png"
+ ],
+ [
+ "Image_10L.jpg",
+ "Image_10L_2ndHO.png",
+ "Image_10L.png"
+ ],
+ [
+ "Image_10R.jpg",
+ "Image_10R_2ndHO.png",
+ "Image_10R.png"
+ ]
+ ]
+}
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/second_annotator.py b/src/mednet/libs/segmentation/config/data/chasedb1/second_annotator.py
new file mode 100644
index 00000000..90c02cff
--- /dev/null
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/second_annotator.py
@@ -0,0 +1,8 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""CHASE-DB1 dataset for Vessel Segmentation."""
+
+from mednet.libs.segmentation.config.data.chasedb1.datamodule import DataModule
+
+datamodule = DataModule("second-annotator.json")
diff --git a/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json b/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json
new file mode 100644
index 00000000..ec8254de
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_chasedb1_first_annotator.json
@@ -0,0 +1,16 @@
+{
+ "train": [
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+}
diff --git a/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_chasedb1_first_annotator.json b/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_chasedb1_first_annotator.json
new file mode 100644
index 00000000..ab664159
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_chasedb1_first_annotator.json
@@ -0,0 +1,16 @@
+{
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+ ]
+}
diff --git a/src/mednet/libs/segmentation/tests/test_chasedb1.py b/src/mednet/libs/segmentation/tests/test_chasedb1.py
new file mode 100644
index 00000000..145bb4db
--- /dev/null
+++ b/src/mednet/libs/segmentation/tests/test_chasedb1.py
@@ -0,0 +1,138 @@
+# SPDX-FileCopyrightText: Copyright © 2024 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+"""Tests for chasedb1 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",
+ [
+ ("first-annotator", dict(train=8, test=20)),
+ ("second-annotator", dict(train=8, 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.segmentation.config.data.chasedb1.datamodule import (
+ make_split,
+ )
+
+ database_checkers.check_split(
+ make_split(f"{split}.json"),
+ lengths=lengths,
+ )
+
+
+@pytest.mark.skip_if_rc_var_not_set("datadir.chasedb1")
+def test_database_check():
+ from mednet.libs.segmentation.scripts.database import check
+
+ runner = CliRunner()
+ result = runner.invoke(check, ["chasedb1"])
+ 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.chasedb1")
+@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",
+ ).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.chasedb1")
+def test_raw_transforms_image_quality(database_checkers, datadir):
+ reference_histogram_file = str(
+ datadir
+ / "histograms/raw_data/histograms_chasedb1_first_annotator.json",
+ )
+
+ datamodule = importlib.import_module(
+ ".first_annotator",
+ "mednet.libs.segmentation.config.data.chasedb1",
+ ).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.chasedb1")
+@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}_chasedb1_first_annotator.json",
+ )
+
+ datamodule = importlib.import_module(
+ ".first_annotator",
+ "mednet.libs.segmentation.config.data.chasedb1",
+ ).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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