[various] Fix multiple import errors after rebase

pyproject.toml

@@ -48,6 +48,7 @@ dependencies = [
   "tensorboard",
   "torchvision~=0.17.2",
   "torch~=2.2.2",
+  "torchio",
   "tqdm",
   "versioningit",
 ]
@@ -104,7 +105,7 @@ tensorboard = "*"
 torchvision = { version = "~=0.17.2", channel = "pytorch" }
 tqdm = "*"
 versioningit = "*"
-torchio = ">=0.19.7,<0.20"
+torchio = "*"
 
 [tool.pixi.feature.self.pypi-dependencies]
 mednet = { path = ".", editable = true }
@@ -248,7 +249,7 @@ densenet = "mednet.libs.classification.config.models.densenet"
 densenet-pretrained = "mednet.libs.classification.config.models.densenet_pretrained"
 
 # 3D models
-cnn3d = "mednet.config.models.cnn3d"
+cnn3d = "mednet.libs.classification.config.models.cnn3d"
 
 # lists of data augmentations
 affine = "mednet.libs.common.config.augmentations.affine"

src/mednet/libs/classification/config/data/visceral/default.py

@@ -3,12 +3,11 @@
 # SPDX-License-Identifier: GPL-3.0-or-later
 """VISCERAL dataset for 3D organ classification.
 
-Database reference:
-
-See :py:class:`mednet.config.data.visceral.datamodule.DataModule` for
-technical details.
+See
+:py:class:`mednet.libs.classification.config.data.visceral.datamodule.DataModule`
+for technical details.
 """
 
-from mednet.config.data.visceral.datamodule import DataModule
+from mednet.libs.classification.config.data.visceral.datamodule import DataModule
 
 datamodule = DataModule("default.json")

src/mednet/libs/classification/config/models/cnn3d.py

 # SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
 #
 # SPDX-License-Identifier: GPL-3.0-or-later
-"""Simple CNN for 3D organ classification, to be trained from scratch."""
+"""Simple CNN for 3D image classification, to be trained from scratch."""
 
-from mednet.models.cnn3d import Conv3DNet
+from mednet.libs.classification.models.cnn3d import Conv3DNet
 from torch.nn import BCEWithLogitsLoss
 from torch.optim import Adam
 

src/mednet/libs/classification/scripts/upload.py

@@ -14,7 +14,7 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
 
 
 @click.command(
-    entry_point_group="mednet.config",
+    entry_point_group="mednet.libs.classification.config",
     cls=ConfigCommand,
     epilog="""Examples:
 

src/mednet/libs/segmentation/scripts/upload.py

@@ -14,7 +14,7 @@ logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
 
 
 @click.command(
-    entry_point_group="mednet.config",
+    entry_point_group="mednet.libs.segmentation.config",
     cls=ConfigCommand,
     epilog="""Examples:
 

tests/classification/test_montgomery_shenzhen_indian_tbx11k.py

@@ -115,7 +115,7 @@ def test_split_consistency(name: str, tbx11k_name: str):
 def test_batch_uniformity(tbx11k_name: str, dataset: str):
     combined = importlib.import_module(
         f".{tbx11k_name}",
-        "mednet.config.data.montgomery_shenzhen_indian_tbx11k",
+        "mednet.libs.classification.config.data.montgomery_shenzhen_indian_tbx11k",
     ).datamodule
 
     combined.model_transforms = []  # should be done before setup()

tests/classification/test_visceral.py

@@ -28,7 +28,7 @@ def test_protocol_consistency(
     from mednet.libs.common.data.split import make_split
 
     database_checkers.check_split(
-        make_split("mednet.config.data.visceral", f"{split}.json"),
+        make_split("mednet.libs.classification.config.data.visceral", f"{split}.json"),
         lengths=lenghts,
         prefixes=("16/10000"),
         possible_labels=(0, 1),