  General Instance Re-identification is a very important task in the computer
vision, which can be widely used in many practical applications, such as
person/vehicle re-identification, face recognition, wildlife protection,
commodity tracing, and snapshop, etc.. To meet the increasing application
demand for general instance re-identification, we present FastReID as a widely
used software system in JD AI Research. In FastReID, highly modular and
extensible design makes it easy for the researcher to achieve new research
ideas. Friendly manageable system configuration and engineering deployment
functions allow practitioners to quickly deploy models into productions. We
have implemented some state-of-the-art projects, including person re-id,
partial re-id, cross-domain re-id and vehicle re-id, and plan to release these
pre-trained models on multiple benchmark datasets. FastReID is by far the most
general and high-performance toolbox that supports single and multiple GPU
servers, you can reproduce our project results very easily and are very welcome
to use it, the code and models are available at
https://github.com/JDAI-CV/fast-reid.
