目标追踪中如何避免车辆过线时的前帧重复结果记录

核心思路是利用ByteTrack生成的唯一跟踪ID，维护一个已计数的ID集合，确保同一辆车只被记录一次：

• 在Camera类中新增集合，存储已经完成过线计数的车辆ID
• 触发过线检测时，先检查当前车辆的跟踪ID是否已在集合中，未存在才执行记录操作
• 视频循环播放时重置集合，避免后续循环的车辆被误判为已计数

修改后的代码 #

第一步：添加已计数ID集合 #

在Camera类中新增类变量：

class Camera(BaseCamera):
    """
    OpenCV video stream
    """
    video_source = 0
    start, end = Point(0, 500), Point(1280, 500)
    detector = Detector()
    tracker = ByteTrack()
    line_zone = LineZone(start=start, end=end)
    annotator = LineZoneAnnotator()
    counted_ids = set()  # 新增：存储已计数的车辆跟踪ID

第二步：修改视频循环逻辑 #

在视频回到第一帧时，清空已计数集合：

# Loop back
if not ret:
    camera.set(cv2.CAP_PROP_POS_FRAMES, 0)
    cls.counted_ids.clear()  # 重置已计数ID，适配视频循环场景
    continue

第三步：过滤重复过线记录 #

在触发过线检测时，判断跟踪ID是否已被记录：

result=cls.line_zone.trigger(detections)
if result is not None and len(result)>=3:
    track_id = result[2]
    if track_id not in cls.counted_ids:
        # 这里替换成你的结果存储逻辑（比如写入数据库/文件）
        print(track_id)
        cls.counted_ids.add(track_id)

完整修改后的Camera类代码 #

class Camera(BaseCamera):
    """
    OpenCV video stream
    """
    video_source = 0
    start, end = Point(0, 500), Point(1280, 500)
    detector = Detector()
    tracker = ByteTrack()
    line_zone = LineZone(start=start, end=end)
    annotator = LineZoneAnnotator()
    counted_ids = set()  # 存储已计数的车辆跟踪ID

    def __init__(self, enable_detection: bool = False):
        video_source = os.environ.get("VIDEO_SOURCE")
        try:
            video_source = int(video_source)
        except Exception as exp:    # pylint: disable=broad-except
            if not video_source:
                raise EnvironmentError("Cannot open the video source!") from exp
        finally:
            Camera.set_video_source(video_source)
        super().__init__()
        self.enable_detection = enable_detection

    @staticmethod
    def set_video_source(source):
        """Set video source"""
        Camera.video_source = source

    @classmethod
    def frames(cls):
        """
        Get video frame
        """
        camera = cv2.VideoCapture(Camera.video_source)
        if not camera.isOpened():
            raise RuntimeError("Could not start camera.")

        while True:
            # read current frame
            ret, img = camera.read()

            # Loop back
            if not ret:
                camera.set(cv2.CAP_PROP_POS_FRAMES, 0)
                cls.counted_ids.clear()  # 重置已计数ID集合
                continue

            # Object detection
            results = cls.detector(image=img)
            selected_classes = [2, 3]

            tensorflow_results = results.detections
            cls.annotator.annotate(img, cls.line_zone)
            if not tensorflow_results:
                yield cv2.imencode(".jpg", img)[1].tobytes()
                continue

            detections = Detections.from_tensorflow(tensorflow_results=tensorflow_results)

            detections = cls.tracker.update_with_detections(detections=detections)
            detections = detections[np.isin(detections.class_id, selected_classes)]
            
            result=cls.line_zone.trigger(detections)
            if result is not None and len(result)>=3:
                track_id = result[2]
                if track_id not in cls.counted_ids:
                    # 替换为你的结果存储逻辑
                    print(track_id)
                    cls.counted_ids.add(track_id)
                
            img = visualize(image=img, detections=detections)

            # encode as a jpeg image and return it
            yield cv2.imencode(".jpg", img)[1].tobytes()

内容的提问来源于stack exchange，提问作者SARON RAVUTH