[config.data.*] Remove center_crop from all raw data loaders to avoid lung cropping (closes #23)

src/mednet/config/data/hivtb/datamodule.py

@@ -12,7 +12,7 @@ import os
 
 import PIL.Image
 
-from torchvision.transforms.functional import center_crop, to_tensor
+from torchvision.transforms.functional import to_tensor
 
 from ....data.datamodule import CachingDataModule
 from ....data.image_utils import remove_black_borders
@@ -58,7 +58,6 @@ class RawDataLoader(_BaseRawDataLoader):
         )
         image = remove_black_borders(image)
         tensor = to_tensor(image)
-        tensor = center_crop(tensor, min(*tensor.shape[1:]))
 
         # use the code below to view generated images
         # from torchvision.transforms.functional import to_pil_image

src/mednet/config/data/montgomery/datamodule.py

@@ -11,7 +11,7 @@ import os
 
 import PIL.Image
 
-from torchvision.transforms.functional import center_crop, to_tensor
+from torchvision.transforms.functional import to_tensor
 
 from ....data.datamodule import CachingDataModule
 from ....data.image_utils import remove_black_borders
@@ -57,7 +57,6 @@ class RawDataLoader(_BaseRawDataLoader):
         image = PIL.Image.open(os.path.join(self.datadir, sample[0]))
         image = remove_black_borders(image)
         tensor = to_tensor(image)
-        tensor = center_crop(tensor, min(*tensor.shape[1:]))
 
         # use the code below to view generated images
         # from torchvision.transforms.functional import to_pil_image

src/mednet/config/data/padchest/datamodule.py

@@ -12,7 +12,7 @@ import os
 import numpy
 import PIL.Image
 
-from torchvision.transforms.functional import center_crop, to_tensor
+from torchvision.transforms.functional import to_tensor
 
 from ....data.datamodule import CachingDataModule
 from ....data.image_utils import remove_black_borders
@@ -59,7 +59,6 @@ class RawDataLoader(_BaseRawDataLoader):
         image = remove_black_borders(image)
         array = numpy.array(image).astype(numpy.float32) / 65535
         tensor = to_tensor(array)
-        tensor = center_crop(tensor, min(*tensor.shape[1:]))
 
         # use the code below to view generated images
         # from torchvision.transforms.functional import to_pil_image

src/mednet/config/data/shenzhen/datamodule.py

@@ -11,7 +11,7 @@ import os
 
 import PIL.Image
 
-from torchvision.transforms.functional import center_crop, to_tensor
+from torchvision.transforms.functional import to_tensor
 
 from ....data.datamodule import CachingDataModule
 from ....data.image_utils import remove_black_borders
@@ -68,7 +68,6 @@ class RawDataLoader(_BaseRawDataLoader):
         )
         image = remove_black_borders(image)
         tensor = to_tensor(image)
-        tensor = center_crop(tensor, min(*tensor.shape[1:]))
 
         # use the code below to view generated images
         # from torchvision.transforms.functional import to_pil_image

src/mednet/config/data/tbpoc/datamodule.py

@@ -7,7 +7,7 @@ import os
 
 import PIL.Image
 
-from torchvision.transforms.functional import center_crop, to_tensor
+from torchvision.transforms.functional import to_tensor
 
 from ....data.datamodule import CachingDataModule
 from ....data.image_utils import remove_black_borders
@@ -53,7 +53,6 @@ class RawDataLoader(_BaseRawDataLoader):
         image = PIL.Image.open(os.path.join(self.datadir, sample[0]))
         image = remove_black_borders(image)
         tensor = to_tensor(image)
-        tensor = center_crop(tensor, min(*tensor.shape[1:]))
 
         # use the code below to view generated images
         # from torchvision.transforms.functional import to_pil_image