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# Ultralytics YOLO π, AGPL-3.0 license | |
from functools import partial | |
import torch | |
from ultralytics.yolo.utils import IterableSimpleNamespace, yaml_load | |
from ultralytics.yolo.utils.checks import check_yaml | |
from .trackers import BOTSORT, BYTETracker | |
TRACKER_MAP = {'bytetrack': BYTETracker, 'botsort': BOTSORT} | |
def on_predict_start(predictor, persist=False): | |
""" | |
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)) | |
assert cfg.tracker_type in ['bytetrack', 'botsort'], \ | |
f"Only support 'bytetrack' and 'botsort' 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) | |
predictor.trackers = trackers | |
def on_predict_postprocess_end(predictor): | |
"""Postprocess detected boxes and update with object tracking.""" | |
bs = predictor.dataset.bs | |
im0s = predictor.batch[1] | |
for i in range(bs): | |
det = predictor.results[i].boxes.cpu().numpy() | |
if len(det) == 0: | |
continue | |
tracks = predictor.trackers[i].update(det, im0s[i]) | |
if len(tracks) == 0: | |
continue | |
idx = tracks[:, -1].astype(int) | |
predictor.results[i] = predictor.results[i][idx] | |
predictor.results[i].update(boxes=torch.as_tensor(tracks[:, :-1])) | |
def register_tracker(model, persist): | |
""" | |
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', on_predict_postprocess_end) | |