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mikel-brostrom / yolo_tracking

BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
GNU Affero General Public License v3.0
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Tiled inference with StrongSort yolo.track method #1402

Closed Asmlatg closed 1 month ago

Asmlatg commented 1 month ago

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Hello, I understand that the architecture of StrongSORT is different from all other trackers (it doesn't have a self.observation like the base class 'BaseTracker'). That's why I'm currently attempting to use YOLO's track method (as it is lightweight compared to directly invoking YOLO and calling prediction methods like it's done in 'Tiled inference'). However, I can't seem to figure out how the IDs are returned from the tracker. Should I call the update method using the correct elements from the variable r in the results (in track.py) and then use the outputs returned by the StrongSORT.update method? Or is it included in the yolo.track method?

mikel-brostrom commented 1 month ago

Just follow the tiled inference examples under README 😄

Asmlatg commented 1 month ago

I did but using yolo.track provided a lightweight result compared to using yolo.predict (like in tiled inference example). So, I wanted to utilize it instead of yolo.predict. Would taking the IDs returned by yolo.track suffice? I attempted to extract the IDs using id = r.boxes.id.cpu().numpy(), but encountered an error.

video 1/1 (11/3766)..: 384x640 10 cars, 74.6ms strong sort called [ 1 2 3 4 5 6 7 8 9 10] video 1/1 (12/3766) .. 384x640 10 cars, 64.8ms strong sort called [ 1 2 3 4 5 6 7 8 9 10 11 12] video 1/1 (13/3766) ...: 384x640 11 cars, 1 truck, 67.3ms strong sort called Traceback (most recent call last): File "tracking/track.py", line 237, in run(opt) File "../lib/python3.8/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(*args, *kwargs) File "tracking/track.py", line 159, in run for r in results: File "../lib/python3.8/site-packages/torch/utils/_contextlib.py", line 56, in generator_context response = gen.send(request) File "..lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 274, in stream_inference self.run_callbacks('on_predict_postprocess_end') File "..lib/python3.8/site-packages/ultralytics/engine/predictor.py", line 377, in run_callbacks callback(self) File "../lib/python3.8/site-packages/ultralytics/trackers/track.py", line 64, in on_predict_postprocess_end predictor.results[i] = predictor.results[i][idx] File "..lib/python3.8/site-packages/ultralytics/engine/results.py", line 108, in getitem return self._apply('getitem', idx) File "..lib/python3.8/site-packages/ultralytics/engine/results.py", line 143, in _apply setattr(r, k, getattr(v, fn)(args, **kwargs)) File "../lib/python3.8/site-packages/ultralytics/engine/results.py", line 63, in getitem return self.class(self.data[idx], self.orig_shape) IndexError: index 9 is out of bounds for dimension 0 with size 9

github-actions[bot] commented 1 month ago

👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs. Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!