FastReID: A Pytorch Toolbox for General Instance Re-identification

4 Jun 2020  ·  Lingxiao He, Xingyu Liao, Wu Liu, Xinchen Liu, Peng Cheng, Tao Mei ·

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.

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Results from the Paper


Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Person Re-Identification Market-1501-C SBS (ResNet-50) Rank-1 34.13 # 7
mAP 11.54 # 8
mINP 0.29 # 13
Person Re-Identification MSMT17-C SBS (ResNet-50) Rank-1 28.77 # 1
mAP 7.89 # 1
mINP 0.05 # 4

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