Update app.py

app.py

@@ -436,17 +436,10 @@ class ForgeryDetector:
             # 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),
-                (tensor_w, tensor_h),
-                interpolation=cv2.INTER_NEAREST
-            )
-            
+            # Pass region_mask directly - feature extractor handles resizing internally
             features = self.feature_extractor.extract(
                 preprocessed_numpy,
-                region_mask_for_features,
+                region['region_mask'],
                 [f.cpu() for f in decoder_features]
             )