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SOTA Re-identification Methods and Toolbox
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README.md

FastReID

FastReID is a research platform that implements state-of-the-art re-identification algorithms. It is a groud-up rewrite of the previous verson, reid strong baseline.

What's New

  • Remove ignite(a high-level library) dependency and powered by PyTorch.
  • Includes more features such as circle loss, abundant visualization methods and evaluation metrics, SoTA results on conventional, cross-domain, partial and vehicle re-id, testing on multi-datasets simultaneously, etc.
  • Can be used as a library to support different projects on top of it. We'll open source more research projects in this way.
  • It trains much faster.

See our zhihu blog to learn more about fastreid.

Installation

See INSTALL.md.

Quick Start

The designed architecture follows this guide PyTorch-Project-Template, you can check each folder's purpose by yourself.

See GETTING_STARTED.md.

Learn more at out documentation. And see projects/ for some projects that are build on top of fastreid.

Model Zoo and Baselines

We provide a large set of baseline results and trained models available for download in the Fastreid Model Zoo.

License

Fastreid is released under the Apache 2.0 license.