Update app.py

app.py

@@ -255,24 +255,25 @@ def get_detection_data(image_data):
 
         detections = []
         for idx, obj in enumerate(objects_data):
-            cls_id, cls_name, center, mask, color_bgr = obj
+            # Unpack all 6 values
+            cls_id, cls_name, center, mask, color_bgr, confidence = obj  
             x1, y1, x2, y2 = get_bbox_from_mask(mask)
             depth_value = depth_at_center(depthmap, [x1, y1, x2, y2])
             
-            # Get color in RGB format (OpenCV uses BGR)
-            color_rgb = (int(color_bgr[2]), int(color_bgr[1]), int(color_bgr[0]))  # Convert BGR to RGB
+            # Convert BGR to RGB
+            color_rgb = (int(color_bgr[2]), int(color_bgr[1]), int(color_bgr[0]))
 
             detections.append({
-                "class_id": cls_id,
-                "class_name": cls_name,
-                "bounding_box": {
-                    "vertices": get_box_vertices([x1, y1, x2, y2])
-                },
-                "position_3d": get_3d_position(center, depth_value, get_camera_matrix(depth_estimator)),
-                "distance": depth_value,
-                "color": color_rgb,
-                "confidence": float(confidence)
-            })
+            "class_id": cls_id,
+            "class_name": cls_name,
+            "bounding_box": {
+                "vertices": get_box_vertices([x1, y1, x2, y2])
+            },
+            "position_3d": get_3d_position(center, depth_value, get_camera_matrix(depth_estimator)),
+            "distance": depth_value,
+            "color": color_rgb,
+            "confidence": float(confidence)
+    })
 
         response = {
             "detections": detections,