Update app.py

app.py

@@ -260,10 +260,16 @@ def get_detection_data(image_data):
             # 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])
+            
+            # Debug: Log original center and vertices (1536x1024)
+            print(f"Debug - Object {idx}: Original Center = {center}, Original Vertices = {get_box_vertices([x1, y1, x2, y2])}")
 
-            # Debug: Log center and vertices to verify resolution
-            print(f"Debug - Object {idx}: Center = {center}, Vertices = {get_box_vertices([x1, y1, x2, y2])}")
+            # Handle invalid or NaN depth values
+            if depth_value is None or np.isnan(depth_value) or not isinstance(depth_value, (int, float)) or depth_value <= 0:
+                print(f"Warning: Invalid depth value ({depth_value}) for Object {idx}. Using default depth of 1.0...")
+                depth_value = 1.0  # Default to 1.0 if depth is invalid or NaN
 
             # Scale from 1536x1024 to 1512x1008, ensuring values fit within bounds
             scale_x = 1512 / 1536  # Width scaling factor
@@ -314,7 +320,7 @@ def get_detection_data(image_data):
                     "vertices": scaled_vertices
                 },
                 "center_2d": scaled_center,  # Use scaled center
-                "distance": depth_value,  # Depth in meters
+                "distance": float(depth_value),  # Ensure depth is a float, not NaN
                 "color": color_rgb,
                 "confidence": float(confidence)