working

services/stream_connection_manager.py

@@ -222,7 +222,17 @@ class StreamConnection:
             # The frame in result["frame"] is preprocessed (resized, normalized)
             # We need the original frame for visualization
             frame_ref = result["metadata"].get("frame_ref")
-            frame_tensor = frame_ref.rgb_tensor if frame_ref else None
+
+            # CRITICAL: Clone the frame tensor BEFORE freeing frame_ref
+            # The frame_ref will be freed at the end, so we need a copy
+            if frame_ref:
+                frame_tensor = frame_ref.rgb_tensor.clone()
+                logger.debug(
+                    f"Cloned frame tensor for {self.stream_id}: {frame_tensor.shape}"
+                )
+            else:
+                frame_tensor = None
+                logger.warning(f"No frame_ref in metadata for {self.stream_id}")
 
             # Create tracking result
             tracking_result = TrackingResult(
@@ -231,7 +241,7 @@ class StreamConnection:
                 tracked_objects=tracked_objects,
                 detections=detections,
                 frame_shape=result["metadata"].get("shape"),
-                frame_tensor=frame_tensor,  # Original frame, not preprocessed
+                frame_tensor=frame_tensor,  # Cloned original frame
                 metadata=result["metadata"],
             )
 

test_tracking_realtime.py

@@ -109,6 +109,10 @@ def main_multi_stream():
     start_time = time.time()
     stats_lock = threading.Lock()
 
+    # Buffer for latest frames (for display in main thread)
+    latest_frames = {}
+    frames_lock = threading.Lock()
+
     # Create windows for each stream if display enabled
     if ENABLE_DISPLAY:
         for stream_id, _ in camera_urls:
@@ -121,13 +125,6 @@ def main_multi_stream():
         """Callback for tracking results - called automatically per stream"""
         nonlocal total_results
 
-        # Debug: Check if we have frame tensor
-        has_frame = result.frame_tensor is not None
-        frame_shape = result.frame_tensor.shape if has_frame else None
-        print(
-            f"[CALLBACK] Got result for {result.stream_id}, has_frame={has_frame}, shape={frame_shape}, detections={len(result.detections)}"
-        )
-
         with stats_lock:
             total_results += 1
             stream_id = result.stream_id
@@ -203,8 +200,9 @@ def main_multi_stream():
                 2,
             )
 
-            # Display
-            cv2.imshow(stream_id, frame_bgr)
+            # Store frame for display in main thread (OpenCV requires this)
+            with frames_lock:
+                latest_frames[stream_id] = frame_bgr
 
     # Connect all streams in parallel using threads
     print(f"\n[3/3] Connecting {len(camera_urls)} streams in parallel...")
@@ -259,6 +257,11 @@ def main_multi_stream():
         # Keep main thread alive and process OpenCV events
         while True:
             if ENABLE_DISPLAY:
+                # Display latest frames from all streams
+                with frames_lock:
+                    for stream_id, frame_bgr in latest_frames.items():
+                        cv2.imshow(stream_id, frame_bgr)
+
                 # Process OpenCV events to keep windows responsive
                 if cv2.waitKey(1) & 0xFF == ord("q"):
                     break