pyproject.toml

@@ -10,7 +10,7 @@ include = '\.pyi?$'
 
 [project]
 name = "aiia"
-version = "0.1.4"
+version = "0.1.5"
 description = "AIIA Deep Learning Model Implementation"
 readme = "README.md"
 authors = [

setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = aiia
-version = 0.1.4
+version = 0.1.5
 author = Falko Habel
 author_email = falko.habel@gmx.de
 description = AIIA deep learning model implementation

src/aiia/__init__.py

@@ -4,4 +4,4 @@ from .data.DataLoader import DataLoader
 from .pretrain.pretrainer import Pretrainer, ProjectionHead
 
 
-__version__ = "0.1.4"
+__version__ = "0.1.5"

src/aiia/data/DataLoader.py

@@ -177,7 +177,7 @@ class AIIADataset(torch.utils.data.Dataset):
         self.items = items
         self.pretraining = pretraining
         self.transform = transforms.Compose([
-            transforms.Resize((384, 384)),
+            transforms.Resize((352, 352)),
             transforms.ToTensor()
         ])
         
@@ -193,7 +193,7 @@ class AIIADataset(torch.utils.data.Dataset):
                 raise ValueError(f"Invalid image at index {idx}")
                 
             image = self.transform(image)
-            if image.shape != (3, 384, 384):
+            if image.shape != (3, 352, 352):
                 raise ValueError(f"Invalid image shape at index {idx}: {image.shape}")
             
             if task == 'denoise':
@@ -215,7 +215,7 @@ class AIIADataset(torch.utils.data.Dataset):
                 if not isinstance(image, Image.Image):
                     raise ValueError(f"Invalid image at index {idx}")
                 image = self.transform(image)
-                if image.shape != (3, 384, 384):
+                if image.shape != (3, 352, 352):
                     raise ValueError(f"Invalid image shape at index {idx}: {image.shape}")
                 return image, label
             else:
@@ -223,6 +223,6 @@ class AIIADataset(torch.utils.data.Dataset):
                     image = self.transform(item)
                 else:
                     image = self.transform(item[0])
-                if image.shape != (3, 384, 384):
+                if image.shape != (3, 352, 352):
                     raise ValueError(f"Invalid image shape at index {idx}: {image.shape}")
                 return image