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Integrate ByteTracker and BoT-SORT trackers (#788)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
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Laughing 2023-02-16 00:23:03 +08:00 • committed by GitHub
parent d99e04daa1
commit ed6c54da7a
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24 changed files with 1635 additions and 19 deletions
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10
ultralytics/yolo/engine/predictor.py
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@ -83,7 +83,6 @@ class BasePredictor:
# Usable if setup is done
self.model = None
self.data = self.args.data # data_dict
self.bs = None
self.imgsz = None
self.device = None
self.classes = self.args.classes
@ -136,7 +135,6 @@ class BasePredictor:
self.vid_path, self.vid_writer = [None] * self.dataset.bs, [None] * self.dataset.bs
def stream_inference(self, source=None, model=None):
self.run_callbacks("on_predict_start")
if self.args.verbose:
LOGGER.info("")
@ -155,6 +153,7 @@ class BasePredictor:
self.done_warmup = True
self.seen, self.windows, self.dt, self.batch = 0, [], (ops.Profile(), ops.Profile(), ops.Profile()), None
self.run_callbacks("on_predict_start")
for batch in self.dataset:
self.run_callbacks("on_predict_batch_start")
self.batch = batch
@ -172,8 +171,12 @@ class BasePredictor:
# postprocess
with self.dt[2]:
self.results = self.postprocess(preds, im, im0s, self.classes)
self.run_callbacks("on_predict_postprocess_end")
# visualize, save, write results
for i in range(len(im)):
p, im0 = (path[i], im0s[i]) if self.source_type.webcam or self.source_type.from_img else (path, im0s)
p, im0 = (path[i], im0s[i].copy()) if self.source_type.webcam or self.source_type.from_img else (path,
im0s)
p = Path(p)
if self.args.verbose or self.args.save or self.args.save_txt or self.args.show:
@ -184,7 +187,6 @@ class BasePredictor:
if self.args.save:
self.save_preds(vid_cap, i, str(self.save_dir / p.name))
self.run_callbacks("on_predict_batch_end")
yield from self.results