Update app.py

app.py

@@ -68,8 +68,11 @@ def predict(image):
         for box, label in zip(boxes, labels):
             x1, y1, x2, y2 = box.astype(int)
             image_np = cv2.rectangle(image_np, (x1, y1), (x2, y2), (255, 0, 0), 2)
-            class_name = COCO_CLASSES[label]  # Get the class name
-            image_np = cv2.putText(image_np, class_name, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 2)
+            if label < len(COCO_CLASSES):  # Ensure label is within bounds
+                class_name = COCO_CLASSES[label]  # Get the class name
+                image_np = cv2.putText(image_np, class_name, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 2)
+            else:
+                print(f"Warning: Label {label} is out of bounds for COCO_CLASSES.")
 
         # Ensure the output is in the correct format
         return Image.fromarray(image_np.astype(np.uint8))