Update app.py

app.py

@@ -30,12 +30,16 @@ def apply_nms(predictions, iou_threshold=0.5):
     # Perform NMS using OpenCV
     indices = cv2.dnn.NMSBoxes(boxes.tolist(), scores.tolist(), score_threshold=0.25, nms_threshold=iou_threshold)
 
-    # Ensure indices are a numpy array (if returned as a tuple)
-    if isinstance(indices, tuple):
-        indices = indices[0]  # Extracting the first element which contains the indices
+    # Check if indices is empty or invalid
+    if not indices or not isinstance(indices, tuple) or len(indices) == 0:
+        print("No valid indices returned from NMS.")
+        return []  # Return an empty list if no valid indices are found
 
-    # Now indices is a numpy array, we can safely call .flatten()
-    indices = indices.flatten()
+    # Extract the indices if they are valid
+    indices = indices[0]  # Extracting the first element which contains the indices
+
+    # Flatten indices array (if returned as a tuple)
+    indices = indices.flatten() if isinstance(indices, np.ndarray) else np.array(indices).flatten()
 
     nms_predictions = []