bytetrack

BoxMOT: Pluggable Python and C++ SOTA multi-object tracking modules with support for axis-aligned and oriented bounding boxes

Trackers gives you clean, modular re-implementations of leading multi-object tracking algorithms released under the permissive Apache 2.0 license. You combine them with any detection model you already use.

A real-time multi-object tracking application in C++17 with Qt and ONNX Runtime that runs a YOLO detector with four pluggable trackers — ByteTrack, OC-SORT, Deep OC-SORT, and DeepSORT.

This repository is forked from shouxieai/tensorRT_Pro, extending it to support a wide range of vision models with high-performance TensorRT C++ inference.

The project can achieve FCWS, LDWS, and LKAS functions solely using only visual sensors. using YOLOv5 / YOLOv5-lite / YOLOv6 / YOLOv7 / YOLOv8 / YOLOv9 / EfficientDet and Ultra-Fast-Lane-Detection-v2 .

C++ implementation of ByteTrack that does not include an object detection algorithm.

分别使用OpenCV、ONNXRuntime部署YOLOX+ByteTrack目标跟踪，包含C++和Python两个版本的程序

基于TensorRT的C++高性能推理库，Yolov10, YoloPv2，Yolov5/7/X/8，RT-DETR，单目标跟踪OSTrack、LightTrack。

PyTorch implementation of YOLOv5, YOLOv6, YOLOv7, YOLOv8, Sort, StrongSort, OcSort, ByteTrack, Norfair

Real-Time Face Recognition use SCRFD, ArcFace, ByteTrack and Similarity Measure

Based on tensorrt v8.0+, deploy detect, pose, segment, tracking of YOLOv8 with C++ and python api.

A blazing-fast, modern C++ multi-object tracking library featuring SORT, ByteTrack, OC-SORT, BoostTrack, and more built for real-time performance, cross-platform deployment, and MOT benchmarks.

Анализ трафика на круговом движении с использованием компьютерного зрения

Integration of YOLOv9 with ByteTracker

Multi-thread tracking of YOLOv5 and ByteTrack implemented by C++, accelerated by TensorRT. YOLOv5 和 ByteTrack 的多线程追踪 C++ 实现, 使用 TensorRT 进行推理加速

A general-purpose real-time streaming media and deep learning inference acceleration framework, supporting H264, H265, AAC, MP4, FLV, RTSP, RTMP, and YOLO.实时流媒体及深度学习推理加速通用处理框架，支持H264、H265、AAC、MP4、FLV、RTSP、RTMP、YOLO。

Tracking-by-Detection形式のMOT(Multi Object Tracking)について、 DetectionとTrackingの処理を分離して寄せ集めたフレームワーク(Tracking-by-Detection method MOT(Multi Object Tracking) is a framework that separates the processing of Detection and Tracking.)

ByteTrack-Eigen is a C++ implementation of the ByteTrack object tracking method, leveraging the Eigen library for high-performance matrix and vector operations.

Packaged version of the ByteTrack repository

Car tracking and car counter implemented with YOLOX, ByteTrack and Pytorch.