Overview
BoT-SORT is a state-of-the-art multi-object tracker designed for detecting and tracking objects in a scene, maintaining unique identifiers for each. It combines motion and appearance information with camera-motion compensation and an accurate Kalman filter. BoT-SORT and BoT-SORT-ReID trackers excel in MOTChallenge datasets, achieving top ranks in MOTA, IDF1, and HOTA metrics. It leverages YOLOX and YOLOv7 for object detection and supports multi-class tracking. The architecture facilitates camera motion compensation using OpenCV's VideoStab Global Motion Estimation. Installation involves setting up a Conda environment, installing PyTorch, and using pip to install necessary packages and dependencies like ByteTrack and FastReID.