- Keep ByteTrack confidence-threshold boundary detections eligible and avoid impossible activation thresholds above score 1.0. - Stop mutating caller-owned detections and assignment cost matrices while preserving matched tracker output. - Filter invalid tensor boxes before Kalman updates and respect minimum consecutive frames on first-frame tensor updates. - Avoids per-call np.arange allocation by cloning detections with slice(None) while preserving non-mutation behavior. - Adds regressions for delayed activation on the second consecutive tensor frame and broader invalid-tensor rejection cases. --------- Co-authored-by: Codex <codex@openai.com> |
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| .. | ||
| __init__.py | ||
| test_byte_tracker.py | ||