cleanup the plasma store when finished with a frame

frigate/object_processing.py

@@ -34,7 +34,9 @@ class TrackedObjectProcessor(threading.Thread):
             'best_objects': {},
             'object_status': defaultdict(lambda: defaultdict(lambda: 'OFF')),
             'tracked_objects': {},
-            'current_frame_time': None
+            'current_frame_time': None,
+            'current_frame': np.zeros((720,1280,3), np.uint8),
+            'object_id': None
         })
         
     def get_best(self, camera, label):
@@ -64,33 +66,40 @@ class TrackedObjectProcessor(threading.Thread):
             object_id_hash = hashlib.sha1(str.encode(f"{camera}{frame_time}"))
             object_id_bytes = object_id_hash.digest()
             object_id = plasma.ObjectID(object_id_bytes)
-            current_frame = self.plasma_client.get(object_id)
+            current_frame = self.plasma_client.get(object_id, timeout_ms=0)
 
-            # draw the bounding boxes on the frame
-            for obj in tracked_objects.values():
-                thickness = 2
-                color = COLOR_MAP[obj['label']]
+            if not current_frame is plasma.ObjectNotAvailable:
+                # draw the bounding boxes on the frame
+                for obj in tracked_objects.values():
+                    thickness = 2
+                    color = COLOR_MAP[obj['label']]
+                    
+                    if obj['frame_time'] != frame_time:
+                        thickness = 1
+                        color = (255,0,0)
+
+                    # draw the bounding boxes on the frame
+                    box = obj['box']
+                    draw_box_with_label(current_frame, box[0], box[1], box[2], box[3], obj['label'], f"{int(obj['score']*100)}% {int(obj['area'])}", thickness=thickness, color=color)
+                    # draw the regions on the frame
+                    region = obj['region']
+                    cv2.rectangle(current_frame, (region[0], region[1]), (region[2], region[3]), (0,255,0), 1)
                 
-                if obj['frame_time'] != frame_time:
-                    thickness = 1
-                    color = (255,0,0)
+                if config['snapshots']['show_timestamp']:
+                    time_to_show = datetime.datetime.fromtimestamp(frame_time).strftime("%m/%d/%Y %H:%M:%S")
+                    cv2.putText(current_frame, time_to_show, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
 
-                # draw the bounding boxes on the frame
-                box = obj['box']
-                draw_box_with_label(current_frame, box[0], box[1], box[2], box[3], obj['label'], f"{int(obj['score']*100)}% {int(obj['area'])}", thickness=thickness, color=color)
-                # draw the regions on the frame
-                region = obj['region']
-                cv2.rectangle(current_frame, (region[0], region[1]), (region[2], region[3]), (0,255,0), 1)
-            
-            if config['snapshots']['show_timestamp']:
-                time_to_show = datetime.datetime.fromtimestamp(frame_time).strftime("%m/%d/%Y %H:%M:%S")
-                cv2.putText(current_frame, time_to_show, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(255, 255, 255), thickness=2)
+                ###
+                # Set the current frame as ready
+                ###
+                self.camera_data[camera]['current_frame'] = current_frame
+                self.camera_data[camera]['current_frame_time'] = frame_time
 
-            ###
-            # Set the current frame as ready
-            ###
-            self.camera_data[camera]['current_frame'] = current_frame
-            self.camera_data[camera]['current_frame_time'] = frame_time
+                # store the object id, so you can delete it at the next loop
+                previous_object_id = self.camera_data[camera]['object_id']
+                if not previous_object_id is None:
+                    self.plasma_client.delete([previous_object_id])
+                self.camera_data[camera]['object_id'] = object_id
             
             ###
             # Maintain the highest scoring recent object and frame for each label
@@ -104,10 +113,10 @@ class TrackedObjectProcessor(threading.Thread):
                     # if the object is a higher score than the current best score 
                     # or the current object is more than 1 minute old, use the new object
                     if obj['score'] > best_objects[obj['label']]['score'] or (now - best_objects[obj['label']]['frame_time']) > 60:
-                        obj['frame'] = np.copy(current_frame)
+                        obj['frame'] = np.copy(self.camera_data[camera]['current_frame'])
                         best_objects[obj['label']] = obj
                 else:
-                    obj['frame'] = np.copy(current_frame)
+                    obj['frame'] = np.copy(self.camera_data[camera]['current_frame'])
                     best_objects[obj['label']] = obj
 
             ###