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Reference for ultralytics/trackers/track.py

Note

This file is available at https://github.com/ultralytics/ultralytics/blob/main/ultralytics/trackers/track.py. If you spot a problem please help fix it by contributing a Pull Request 🛠️. Thank you 🙏!



ultralytics.trackers.track.on_predict_start(predictor, persist=False)

Initialize trackers for object tracking during prediction.

Parameters:

Name Type Description Default
predictor object

The predictor object to initialize trackers for.

required
persist bool

Whether to persist the trackers if they already exist. Defaults to False.

False

Raises:

Type Description
AssertionError

If the tracker_type is not 'bytetrack' or 'botsort'.

Source code in ultralytics/trackers/track.py
def on_predict_start(predictor: object, persist: bool = False) -> None:
    """
    Initialize trackers for object tracking during prediction.

    Args:
        predictor (object): The predictor object to initialize trackers for.
        persist (bool, optional): Whether to persist the trackers if they already exist. Defaults to False.

    Raises:
        AssertionError: If the tracker_type is not 'bytetrack' or 'botsort'.
    """
    if hasattr(predictor, "trackers") and persist:
        return

    tracker = check_yaml(predictor.args.tracker)
    cfg = IterableSimpleNamespace(**yaml_load(tracker))

    if cfg.tracker_type not in {"bytetrack", "botsort"}:
        raise AssertionError(f"Only 'bytetrack' and 'botsort' are supported for now, but got '{cfg.tracker_type}'")

    trackers = []
    for _ in range(predictor.dataset.bs):
        tracker = TRACKER_MAP[cfg.tracker_type](args=cfg, frame_rate=30)
        trackers.append(tracker)
        if predictor.dataset.mode != "stream":  # only need one tracker for other modes.
            break
    predictor.trackers = trackers
    predictor.vid_path = [None] * predictor.dataset.bs  # for determining when to reset tracker on new video



ultralytics.trackers.track.on_predict_postprocess_end(predictor, persist=False)

Postprocess detected boxes and update with object tracking.

Parameters:

Name Type Description Default
predictor object

The predictor object containing the predictions.

required
persist bool

Whether to persist the trackers if they already exist. Defaults to False.

False
Source code in ultralytics/trackers/track.py
def on_predict_postprocess_end(predictor: object, persist: bool = False) -> None:
    """
    Postprocess detected boxes and update with object tracking.

    Args:
        predictor (object): The predictor object containing the predictions.
        persist (bool, optional): Whether to persist the trackers if they already exist. Defaults to False.
    """
    path, im0s = predictor.batch[:2]

    is_obb = predictor.args.task == "obb"
    is_stream = predictor.dataset.mode == "stream"
    for i in range(len(im0s)):
        tracker = predictor.trackers[i if is_stream else 0]
        vid_path = predictor.save_dir / Path(path[i]).name
        if not persist and predictor.vid_path[i if is_stream else 0] != vid_path:
            tracker.reset()
            predictor.vid_path[i if is_stream else 0] = vid_path

        det = (predictor.results[i].obb if is_obb else predictor.results[i].boxes).cpu().numpy()
        if len(det) == 0:
            continue
        tracks = tracker.update(det, im0s[i])
        if len(tracks) == 0:
            continue
        idx = tracks[:, -1].astype(int)
        predictor.results[i] = predictor.results[i][idx]

        update_args = {"obb" if is_obb else "boxes": torch.as_tensor(tracks[:, :-1])}
        predictor.results[i].update(**update_args)



ultralytics.trackers.track.register_tracker(model, persist)

Register tracking callbacks to the model for object tracking during prediction.

Parameters:

Name Type Description Default
model object

The model object to register tracking callbacks for.

required
persist bool

Whether to persist the trackers if they already exist.

required
Source code in ultralytics/trackers/track.py
def register_tracker(model: object, persist: bool) -> None:
    """
    Register tracking callbacks to the model for object tracking during prediction.

    Args:
        model (object): The model object to register tracking callbacks for.
        persist (bool): Whether to persist the trackers if they already exist.
    """
    model.add_callback("on_predict_start", partial(on_predict_start, persist=persist))
    model.add_callback("on_predict_postprocess_end", partial(on_predict_postprocess_end, persist=persist))





Created 2023-11-12, Updated 2024-06-02
Authors: glenn-jocher (5), Burhan-Q (1), Laughing-q (1)