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bot_sort - Ultralytics YOLOv8 Docs

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This file is available at https://github.com/ultralytics/ultralytics/blob/main/ultralytics/trackers/bot_sort.py. If you spot a problem please help fix it by contributing a Pull Request 🛠️. Thank you 🙏! Bases: STrack An extended version of the STrack class for YOLOv8, adding object tracking features. Attributes: A shared Kalman filter for all instances of BOTrack. Smoothed feature vector. Current feature vector. A deque to store feature vectors with a maximum length defined by feat_history. Smoothing factor for the exponential moving average of features. The mean state of the Kalman filter. The covariance matrix of the Kalman filter. Methods: Update features vector and smooth it using exponential moving average. Predicts the mean and covariance using Kalman filter. Reactivates a track with updated features and optionally new ID. Update the YOLOv8 instance with new track and frame ID. Property that gets the current position in tlwh format (top left x, top left y, width, height). Predic

Link to this section Reference for ultralytics/trackers/bot_sort.py # Improvements This page is sourced from https://github.com/ultralytics/ultralytics/blob/main/ultralytics/trackers/bot_sort.py . Have an improvement or example to add? Open a Pull Request — thank you! 🙏 Summary Classes Properties Methods BOTrack BOTSORT Link to this section Class ultralytics.trackers.bot_sort.BOTrack # BOTrack(self, xywh: np.ndarray, score: float, cls: int, feat: np.ndarray | None = None) Bases: STrack An extended version of the STrack class for YOLO, adding object tracking features. This class extends the ST

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