BoxMOT: Pluggable Python and C++ SOTA multi-object tracking modules with support for axis-aligned and oriented bounding boxes
- Updated
Oct 20, 2026 - Python
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.
YOLO Vision Studio: a free, open-source Streamlit app for detection, segmentation, pose, text prompts (YOLO World, YOLOE) and tracking with honest counts. Built on Ultralytics YOLO26.
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。
19 ready-to-run computer vision projects with YOLO, ByteTrack & MediaPipe — counting, safety, ANPR, heatmaps and more
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.