Update app.py

app.py

@@ -432,17 +432,20 @@ class ForgeryDetector:
 
             region_mask = region_mask.astype(bool)
             
-            # Extract features using PREPROCESSED image (matches training)
-            # Resize region_mask to match preprocessed dimensions (384x384)
-            preprocessed_h, preprocessed_w = preprocessed.shape[:2]
+            # Extract features using tensor converted to numpy (matches training pipeline)
+            # Convert tensor back to numpy: (C, H, W) -> (H, W, C)
+            preprocessed_numpy = image_tensor[0].permute(1, 2, 0).cpu().numpy()
+            
+            # Resize region_mask to match tensor dimensions
+            tensor_h, tensor_w = preprocessed_numpy.shape[:2]
             region_mask_for_features = cv2.resize(
                 region['region_mask'].astype(np.uint8),
-                (preprocessed_w, preprocessed_h),
+                (tensor_w, tensor_h),
                 interpolation=cv2.INTER_NEAREST
             )
             
             features = self.feature_extractor.extract(
-                preprocessed,
+                preprocessed_numpy,
                 region_mask_for_features,
                 [f.cpu() for f in decoder_features]
             )