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liaoxingyu a1cb123cfa fix R101 bottleneck missing problem

Summary: add key 101 in block dict to support R101

2020-05-26 14:48:32 +08:00

configs

fix: modify open_layers in BoT config file

2020-05-19 14:46:35 +08:00

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docs: update README

2020-05-12 23:00:15 +08:00

demo

fix: remove prefetcher, put normalizer in model

2020-05-25 23:39:11 +08:00

fastreid

fix R101 bottleneck missing problem

2020-05-26 14:48:32 +08:00

projects

feat: partial reid first commit

2020-05-21 23:58:35 +08:00

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update version0.2 code

2020-03-25 10:58:26 +08:00

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fix: add a simple way to reset data prefetcher when resume training

2020-05-09 11:58:27 +08:00

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2020-02-18 21:01:23 +08:00

GETTING_STARTED.md

docs: update README

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Change VehilcleID results

2020-05-25 16:36:08 +08:00

README.md

docs: update README

2020-05-12 23:00:15 +08:00

README.md

FastReID

FastReID is a research platform that implements state-of-the-art re-identification algorithms.

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.

Install dependencies:

pytorch 1.0.0+
torchvision
yacs

Model Zoo and Baselines

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

Languages

Python 86.7%

C++ 11%

Cython 1.3%

CMake 0.6%

Dockerfile 0.4%