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OpenGait is a flexible and extensible gait recognition project provided by the [Shiqi Yu Group](https://faculty.sustech.edu.cn/yusq/) and supported in part by [WATRIX.AI](http://www.watrix.ai).


## What's New
- [Jul 2022] Our paper "[GaitEdge: Beyond Plain End-to-end Gait Recognition for Better Practicality](configs/gaitedge/README.md)" has been accepted by ECCV 2022.
- [Jun 2022] Paper "[A Comprehensive Survey on Deep Gait Recognition: Algorithms, Datasets and Challenges](https://arxiv.org/pdf/2206.13732.pdf)" is available now.
- [Jun 2022] Paper "[Learning Gait Representation from Massive Unlabelled Walking Sequences: A Benchmark](https://arxiv.org/pdf/2206.13964.pdf)" is available now. And the code will be released as soon as possible.
- [Mar 2022] More results on [GREW](https://www.grew-benchmark.org) are supported, and the model files are coming soon.
- [Mar 2022] Dataset [GREW](https://www.grew-benchmark.org) is supported in [datasets/GREW](./datasets/GREW).
- [Mar 2022] [HID](http://hid2022.iapr-tc4.org/) support is ready in [datasets/HID](./datasets/HID).

## Highlighted features
- **Mutiple Dataset supported**: OpenGait supports four popular gait datasets: [CASIA-B](http://www.cbsr.ia.ac.cn/english/Gait%20Databases.asp), [OUMVLP](http://www.am.sanken.osaka-u.ac.jp/BiometricDB/GaitMVLP.html), [HID](http://hid2022.iapr-tc4.org/), and [GREW](https://www.grew-benchmark.org).
- **Multiple Models Support**: We reproduced several SOTA methods, and reached the same or even the better performance. 
- **DDP Support**: The officially recommended [`Distributed Data Parallel (DDP)`](https://pytorch.org/tutorials/intermediate/ddp_tutorial.html) mode is used during both the training and testing phases.
- **AMP Support**: The [`Auto Mixed Precision (AMP)`](https://pytorch.org/tutorials/recipes/recipes/amp_recipe.html?highlight=amp) option is available.
- **Nice log**: We use [`tensorboard`](https://pytorch.org/docs/stable/tensorboard.html) and `logging` to log everything, which looks pretty.

## Getting Started


Please see [0.get_started.md](docs/0.get_started.md). We also provide the following tutorials for your reference:
- [Prepare dataset](docs/2.prepare_dataset.md)
- [Detailed configuration](docs/3.detailed_config.md)
- [Customize model](docs/4.how_to_create_your_model.md)
- [Advanced usages](docs/5.advanced_usages.md) 

## Model Zoo
Results and models are available in the [model zoo](docs/1.model_zoo.md).


## Authors:
**Open Gait Team (OGT)**
- [Chao Fan (樊超)](https://faculty.sustech.edu.cn/?p=128578&tagid=yusq&cat=2&iscss=1&snapid=1&orderby=date), 12131100@mail.sustech.edu.cn
- [Chuanfu Shen (沈川福)](https://faculty.sustech.edu.cn/?p=95396&tagid=yusq&cat=2&iscss=1&snapid=1&orderby=date), 11950016@mail.sustech.edu.cn
- [Junhao Liang (梁峻豪)](https://faculty.sustech.edu.cn/?p=95401&tagid=yusq&cat=2&iscss=1&snapid=1&orderby=date), 12132342@mail.sustech.edu.cn

## Acknowledgement
- GLN: [Saihui Hou (侯赛辉)](http://home.ustc.edu.cn/~saihui/index_english.html)
- GaitGL: [Beibei Lin (林贝贝)](https://scholar.google.com/citations?user=KyvHam4AAAAJ&hl=en&oi=ao)
- GREW: [GREW TEAM](https://www.grew-benchmark.org)
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**Note:**
This code is only used for **academic purposes**, people cannot use this code for anything that might be considered commercial use.