proper image transformation

src/aiia/data/DataLoader.py

@@ -152,10 +152,13 @@ class AIIADataLoader:
     def _create_subset(self, indices):
         subset_items = [self.items[i] for i in indices]
         return AIIADataset(subset_items)
-    
+
 class AIIADataset(torch.utils.data.Dataset):
     def __init__(self, items):
         self.items = items
+        self.transform = transforms.Compose([
+            transforms.ToTensor()
+        ])
         
     def __len__(self):
         return len(self.items)
@@ -164,9 +167,14 @@ class AIIADataset(torch.utils.data.Dataset):
         item = self.items[idx]
         if isinstance(item, tuple) and len(item) == 2:
             image, label = item
+            # Convert PIL image to tensor
+            image = self.transform(image)
             return (image, label)
         elif isinstance(item, tuple) and len(item) == 3:
             image, task, label = item
+            # Convert PIL image to tensor first
+            image = self.transform(image)
+            
             if task == 'denoise':
                 noise_std = 0.1
                 noisy_img = image + torch.randn_like(image) * noise_std
@@ -182,6 +190,7 @@ class AIIADataset(torch.utils.data.Dataset):
                 raise ValueError(f"Unknown task: {task}")
         else:
             if isinstance(item, Image.Image):
-                return item
+                # Convert single PIL image to tensor
+                return self.transform(item)
             else:
-                raise ValueError("Invalid item format.")
+                raise ValueError("Invalid item format.")