diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index c9ae0016c90b88658cbab481bf880ef729a38ce1..25425691057398ffc6c65bda57575ade1d40c97e 100644
--- a/.gitlab-ci.yml
+++ b/.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:
diff --git a/.reuse/dep5 b/.reuse/dep5
index 5314ea6e597528ba571ecdaa3e5686b76102efe5..fb27b959e3ce20f1d74e7f560f752367575d2924 100644
--- a/.reuse/dep5
+++ b/.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
diff --git a/src/mednet/models/pasa.py b/src/mednet/models/pasa.py
index 38ad0218ffd8a0a35573896175d32d9ff6a521af..e285bf7baa36a9ab548de01451622ee61ae1c111 100644
--- a/src/mednet/models/pasa.py
+++ b/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
diff --git a/tests/conftest.py b/tests/conftest.py
index ef45a883f7b7797facac85b4446574c64b806ebe..b51eafa681ca9c95be145a2c5eedea0b1fe5a5b8 100644
--- a/tests/conftest.py
+++ b/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
diff --git a/tests/data/mednet.toml b/tests/data/mednet.toml
new file mode 100644
index 0000000000000000000000000000000000000000..1eccba371435f50739c65227ae46bbae4d33375a
--- /dev/null
+++ b/tests/data/mednet.toml
@@ -0,0 +1,5 @@
+[datadir]
+montgomery = "/idiap/resource/database/MontgomeryXraySet"
+shenzhen = "/idiap/resource/database/ShenzhenXraySet"
+indian = "/idiap/resource/database/TBXpredict"
+tbx11k = "/idiap/resource/database/tbx11k"
diff --git a/tests/test_montgomery.py b/tests/test_montgomery.py
index 44ff9e5141dcd88091c84d3a012dc9e57a2c9645..4ce6258064a64507ccdc2714b9aa16c957961a36 100644
--- a/tests/test_montgomery.py
+++ b/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,
+ )