| cfg | ||
| tracker | ||
| utils | ||
| .gitignore | ||
| demo.py | ||
| extract_ped_per_frame.py | ||
| LICENSE | ||
| models.py | ||
| README.md | ||
| test.py | ||
| track.py | ||
| train.py | ||
Towards-Realtime-MOT
Introduction
This repo is the a codebase of the Joint Detection and Embedding (JDE) model. JDE is a fast and high-performance multiple-object tracker that learns the object detection task and appearance embedding task simutaneously in a shared neural network. Techical details are described in our arXiv preprint paper. By using this repo, you can simply achieve MOTA 64%+ on the "private" protocol of MOT-16 challenge, and with a near real-time speed at 18~24 FPS (Note this speed is for the entire system, including the detection step! ) .
We hope this repo will help researches/engineers to develop more practical MOT systems. For algorithm development, we provide training data, baseline models and evaluation methods to make a level playground. For application usage, we also provide a small video demo that takes a raw video as input without any bells and whistles.