diff --git a/pyproject.toml b/pyproject.toml
index 047778af190c7be4cefd5a8abb6c80d10eff8789..432ecb6bb08a75f9a8178eabdfcc3bd8ee521248 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -429,7 +429,7 @@ driu-pix = "mednet.libs.segmentation.config.models.driu_pix"
hed = "mednet.libs.segmentation.config.models.hed"
lwnet = "mednet.libs.segmentation.config.models.lwnet"
m2unet = "mednet.libs.segmentation.config.models.m2unet"
-resunet = "mednet.libs.segmentation.config.models.resunet"
+#resunet = "mednet.libs.segmentation.config.models.resunet"
unet = "mednet.libs.segmentation.config.models.unet"
# chase-db1 - retinography
diff --git a/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py b/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py
index e635ea2903b5a05c174c2b4686935bd3b9f8178f..73c400be1a7ecb176eb2ed97ba6119d8d81135a3 100644
--- a/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py
+++ b/src/mednet/libs/segmentation/config/data/chasedb1/datamodule.py
@@ -11,6 +11,7 @@ import pkg_resources
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,
)
@@ -54,21 +55,20 @@ class SegmentationRawDataLoader(_SegmentationRawDataLoader):
The sample representation.
"""
- image = PIL.Image.open(self.datadir / sample[0]).convert(mode="RGB")
- tensor = tv_tensors.Image(to_tensor(image))
- target = tv_tensors.Image(
- to_tensor(
- PIL.Image.open(self.datadir / sample[1]).convert(mode="1", dither=None)
- )
+ 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 = tv_tensors.Mask(
- to_tensor(
- PIL.Image.open(self._pkg_path / sample[2]).convert(
- mode="1", dither=None
- )
- )
+
+ mask = to_tensor(
+ PIL.Image.open(self._pkg_path / 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]
diff --git a/src/mednet/libs/segmentation/config/data/refuge/datamodule.py b/src/mednet/libs/segmentation/config/data/refuge/datamodule.py
index 665db0de8f06a1ceaee7f129ca8086f1219d43a3..1fa3e7d5c3c73b0a2d98524a3c3a4d60653b47bb 100644
--- a/src/mednet/libs/segmentation/config/data/refuge/datamodule.py
+++ b/src/mednet/libs/segmentation/config/data/refuge/datamodule.py
@@ -11,6 +11,7 @@ import pkg_resources
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,
)
@@ -87,9 +88,9 @@ class SegmentationRawDataLoader(_SegmentationRawDataLoader):
PIL.Image.open(self._pkg_path / sample[2]).convert(mode="1", dither=None)
)
- tensor = tv_tensors.Image(image)
- target = tv_tensors.Image(target)
- mask = tv_tensors.Mask(mask)
+ 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]
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diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks copy/Training400/Non-Glaucoma/n0356.png b/src/mednet/libs/segmentation/config/data/refuge/masks copy/Training400/Non-Glaucoma/n0356.png
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diff --git a/src/mednet/libs/segmentation/config/data/refuge/masks copy/Training400/Non-Glaucoma/n0360.png b/src/mednet/libs/segmentation/config/data/refuge/masks copy/Training400/Non-Glaucoma/n0360.png
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diff --git a/src/mednet/libs/segmentation/config/data/shenzhen/datamodule.py b/src/mednet/libs/segmentation/config/data/shenzhen/datamodule.py
index fc52054fb577068554b3c259031d33673a3def61..bbb44b3e94687eb296f43d551b3d5507525b1fd9 100644
--- a/src/mednet/libs/segmentation/config/data/shenzhen/datamodule.py
+++ b/src/mednet/libs/segmentation/config/data/shenzhen/datamodule.py
@@ -11,6 +11,7 @@ import torch
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,
)
@@ -56,9 +57,11 @@ class SegmentationRawDataLoader(_SegmentationRawDataLoader):
PIL.Image.open(self.datadir / sample[1]).convert(mode="1", dither=None)
)
- tensor = tv_tensors.Image(image)
- target = tv_tensors.Image(target)
- mask = tv_tensors.Mask(torch.ones_like(target))
+ mask = torch.ones_like(target)
+
+ 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]
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
index 104ad54d7d94358f72eb83e27e1ab13c5adfd0a1..ce6103c027fdbee90f8858b79c121ae6f42bb35e 100644
--- 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
@@ -1,16 +1,16 @@
{
"train": [
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}
diff --git a/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_refuge_cup.json b/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_refuge_cup.json
index 7a8050673cee5cbee984d02cda2c6b5c7bb5278f..b42ec4e7bd8ac354085c217519770ac92af642c1 100644
--- a/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_refuge_cup.json
+++ b/src/mednet/libs/segmentation/tests/data/histograms/models/histograms_lwnet_refuge_cup.json
@@ -1,23 +1,23 @@
{
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],
"test": [
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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
index ab664159fad42eaf3975e49d1cc676e01db66454..43b0886e30c4274b5df87a7c2ffc3c5ce8430d79 100644
--- 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
@@ -1,16 +1,16 @@
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}
diff --git a/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_refuge_cup.json b/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_refuge_cup.json
index 64df6a37635c2b29fd86189047c2d64a01778dbe..c76f850f40dd6287c9e04aa60baceb15f166b24d 100644
--- a/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_refuge_cup.json
+++ b/src/mednet/libs/segmentation/tests/data/histograms/raw_data/histograms_refuge_cup.json
@@ -1,23 +1,23 @@
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],
"test": [
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