Merge branch 'ci-db-paths' into 'update-tests'

Fix Issues when running tests on the CI

See merge request biosignal/software/mednet!19

.gitlab-ci.yml

@@ -10,6 +10,7 @@ include:
 variables:
   GIT_SUBMODULE_STRATEGY: normal
   GIT_SUBMODULE_DEPTH: 1
+  XDG_CONFIG_HOME: $CI_PROJECT_DIR/tests/data
 
 documentation:
   before_script:

.reuse/dep5

@@ -21,5 +21,6 @@ Files:
  tests/data/*.csv
  tests/data/*.json
  tests/data/*.png
+ tests/*.toml
 Copyright: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
 License: GPL-3.0-or-later

src/mednet/models/pasa.py

@@ -75,7 +75,11 @@ class Pasa(pl.LightningModule):
         self.model_transforms = [
             Grayscale(),
             SquareCenterPad(),
-            torchvision.transforms.Resize(512, antialias=True),
+            torchvision.transforms.Resize(
+                512,
+                antialias=True,
+                interpolation=torchvision.transforms.InterpolationMode.BILINEAR,
+            ),
         ]
 
         self._train_loss = train_loss

tests/conftest.py

@@ -2,18 +2,13 @@
 #
 # SPDX-License-Identifier: GPL-3.0-or-later
 
-import os
 import pathlib
-import tempfile
 import typing
-import zipfile
 
+import numpy
 import pytest
-import tomli_w
 import torch
 
-from torchvision.transforms.functional import to_pil_image
-
 from mednet.data.split import JSONDatabaseSplit
 from mednet.data.typing import DatabaseSplit
 
@@ -100,55 +95,6 @@ def temporary_basedir(tmp_path_factory):
     return tmp_path_factory.mktemp("test-cli")
 
 
-def pytest_sessionstart(session: pytest.Session) -> None:
-    """Preset the session start to ensure the Montgomery dataset is always available.
-
-    Parameters
-    ----------
-    session
-        The session to use.
-    """
-
-    from mednet.utils.rc import load_rc
-
-    rc = load_rc()
-
-    database_dir = rc.get("datadir.montgomery")
-    if database_dir is not None:
-        # if the user downloaded it, use that copy
-        return
-
-    # else, we must extract the LFS component (we are likely on the CI)
-    archive = (
-        pathlib.Path(__file__).parents[0] / "data" / "lfs" / "test-database.zip"
-    )
-    assert archive.exists(), (
-        f"Neither datadir.montgomery is set on the global configuration, "
-        f"(typically ~/.config/mednet.toml), or it is possible to detect "
-        f"the presence of {archive}' (did you git submodule init --update "
-        f"this submodule?)"
-    )
-
-    montgomery_tempdir = tempfile.TemporaryDirectory()
-    rc.setdefault("datadir.montgomery", montgomery_tempdir.name)
-
-    with zipfile.ZipFile(archive) as zf:
-        zf.extractall(montgomery_tempdir.name)
-
-    config_filename = "mednet.toml"
-    with open(
-        os.path.join(montgomery_tempdir.name, config_filename), "wb"
-    ) as f:
-        tomli_w.dump(rc.data, f)
-        f.flush()
-
-    os.environ["XDG_CONFIG_HOME"] = montgomery_tempdir.name
-
-    # stash the newly created temporary directory so we can erase it when the
-    key = pytest.StashKey[tempfile.TemporaryDirectory]()
-    session.stash[key] = montgomery_tempdir
-
-
 class DatabaseCheckers:
     """Helpers for database tests."""
 
@@ -256,7 +202,12 @@ class DatabaseCheckers:
         # __import__("pdb").set_trace()
 
     @staticmethod
-    def check_image_quality(datamodule, reference_histogram_file):
+    def check_image_quality(
+        datamodule,
+        reference_histogram_file,
+        compare_type="equal",
+        pearson_coeff_threshold=0.005,
+    ):
         ref_histogram_splits = JSONDatabaseSplit(reference_histogram_file)
 
         for split_name in ref_histogram_splits:
@@ -277,10 +228,28 @@ class DatabaseCheckers:
                 image_tensor = datamodule._datasets[split_name][
                     dataset_sample_index
                 ][0]
-                img = to_pil_image(image_tensor)
-                histogram = img.histogram()
 
-                assert histogram == ref_hist_data
+                histogram = []
+                for color_channel in image_tensor:
+                    color_channel = numpy.multiply(
+                        color_channel.numpy(), 255
+                    ).astype(int)
+                    histogram.extend(
+                        numpy.histogram(
+                            color_channel, bins=256, range=(0, 256)
+                        )[0].tolist()
+                    )
+
+                if compare_type == "statistical":
+                    # Compute pearson coefficients between histogram and reference
+                    # and check the similarity within a certain threshold
+                    pearson_coeffs = numpy.corrcoef(histogram, ref_hist_data)
+                    assert (
+                        1 - pearson_coeff_threshold <= pearson_coeffs[0][1] <= 1
+                    )
+
+                else:
+                    assert histogram == ref_hist_data
 
 
 @pytest.fixture

tests/data/mednet.toml

+[datadir]
+montgomery = "/idiap/resource/database/MontgomeryXraySet"
+shenzhen = "/idiap/resource/database/ShenzhenXraySet"
+indian = "/idiap/resource/database/TBXpredict"
+tbx11k = "/idiap/resource/database/tbx11k"

tests/test_montgomery.py

@@ -95,7 +95,7 @@ def test_loading(database_checkers, name: str, dataset: str):
 
 
 @pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
-def test_loaded_image_quality(database_checkers, datadir):
+def test_raw_transforms_image_quality(database_checkers, datadir):
     reference_histogram_file = str(
         datadir / "histograms/raw_data/histograms_montgomery_default.json"
     )
@@ -142,4 +142,10 @@ def test_model_transforms_image_quality(database_checkers, datadir, model_name):
 
     datamodule.model_transforms = model.model_transforms
     datamodule.setup("predict")
-    database_checkers.check_image_quality(datamodule, reference_histogram_file)
+
+    database_checkers.check_image_quality(
+        datamodule,
+        reference_histogram_file,
+        compare_type="statistical",
+        pearson_coeff_threshold=0.005,
+    )