open-mmlab · YuanLiuuuuuu · May 30, 2022 · May 26, 2022 · May 26, 2022 · May 26, 2022
diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md
@@ -0,0 +1 @@
+We appreciate all contributions to improve MMSelfSup. Please refer to [CONTRIBUTING.md](https://github.com/open-mmlab/mmcv/blob/master/CONTRIBUTING.md) in MMCV for more details about the contributing guideline.
diff --git a/README.md b/README.md
@@ -33,10 +33,14 @@
 
 </div>
 
-## Introduction
+<div align="center">
 
 English | [简体中文](README_zh-CN.md)
 
+</div>
+
+## Introduction
+
 MMSelfSup is an open source self-supervised representation learning toolbox based on PyTorch. It is a part of the [OpenMMLab](https://openmmlab.com/) project.
 
 The master branch works with **PyTorch 1.5** or higher.
@@ -59,11 +63,7 @@ The master branch works with **PyTorch 1.5** or higher.
 
   Since MMSelfSup adopts similar design of modulars and interfaces as those in other OpenMMLab projects, it supports smooth evaluation on downstream tasks with other OpenMMLab projects like object detection and segmentation.
 
-## License
-
-This project is released under the [Apache 2.0 license](LICENSE).
-
-## ChangeLog
+## What's New
 
 MMSelfSup **v0.9.0** was released in 29/04/2022.
 
@@ -76,17 +76,39 @@ Please refer to [changelog.md](docs/en/changelog.md) for details and release his
 
 Differences between MMSelfSup and OpenSelfSup codebases can be found in [compatibility.md](docs/en/compatibility.md).
 
-## Model Zoo and Benchmark
+## Installation
+
+MMSelfSup depends on [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv) and [MMClassification](https://github.com/open-mmlab/mmclassification).
+
+Please refer to [install.md](docs/en/install.md) for more detailed instruction.
+
+## Get Started
+
+Please refer to [prepare_data.md](docs/en/prepare_data.md) for dataset preparation and [get_started.md](docs/en/get_started.md) for the basic usage of MMSelfSup.
+
+We also provides tutorials for more details:
+
+- [config](docs/en/tutorials/0_config.md)
+- [add new dataset](docs/en/tutorials/1_new_dataset.md)
+- [data pipeline](docs/en/tutorials/2_data_pipeline.md)
+- [add new module](docs/en/tutorials/3_new_module.md)
+- [customize schedules](docs/en/tutorials/4_schedule.md)
+- [customize runtime](docs/en/tutorials/5_runtime.md)
+- [benchmarks](docs/en/tutorials/6_benchmarks.md)
+
+Besides, we provide [colab tutorial](https://github.com/open-mmlab/mmselfsup/blob/master/demo/mmselfsup_colab_tutorial.ipynb) for basic usage.
+
+Please refer to [FAQ](docs/en/faq.md) for frequently asked questions.
 
-### Model Zoo
+## Model Zoo
 
 Please refer to [model_zoo.md](docs/en/model_zoo.md) for a comprehensive set of pre-trained models and benchmarks.
 
 Supported algorithms:
 
 - [x] [Relative Location (ICCV'2015)](https://arxiv.org/abs/1505.05192)
 - [x] [Rotation Prediction (ICLR'2018)](https://arxiv.org/abs/1803.07728)
-- [x] [DeepCLuster (ECCV'2018)](https://arxiv.org/abs/1807.05520)
+- [x] [DeepCluster (ECCV'2018)](https://arxiv.org/abs/1807.05520)
 - [x] [NPID (CVPR'2018)](https://arxiv.org/abs/1805.01978)
 - [x] [ODC (CVPR'2020)](https://arxiv.org/abs/2006.10645)
 - [x] [MoCo v1 (CVPR'2020)](https://arxiv.org/abs/1911.05722)
@@ -104,7 +126,7 @@ Supported algorithms:
 
 More algorithms are in our plan.
 
-### Benchmark
+## Benchmark
 
 | Benchmarks                                         | Setting                                                                                                                                                              |
 | -------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
@@ -120,27 +142,16 @@ More algorithms are in our plan.
 | Cityscapes Segmentation                            | [MMSeg](configs/benchmarks/mmsegmentation/cityscapes/fcn_r50-d8_769x769_40k_cityscapes.py)                                                                           |
 | PASCAL VOC12 Aug Segmentation                      | [MMSeg](configs/benchmarks/mmsegmentation/voc12aug/fcn_r50-d8_512x512_20k_voc12aug.py)                                                                               |
 
-## Installation
-
-MMSelfSup depends on [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv) and [MMClassification](https://github.com/open-mmlab/mmclassification).
-
-Please refer to [install.md](docs/en/install.md) for more detailed instruction.
-
-## Get Started
+## Contributing
 
-Please refer to [prepare_data.md](docs/en/prepare_data.md) for dataset preparation and [getting_started.md](docs/en/getting_started.md) for the basic usage of MMSelfSup.
+We appreciate all contributions improving MMSelfSup. Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for more details about the contributing guideline.
 
-We also provides tutorials for more details:
+## Acknowledgement
 
-- [config](docs/en/tutorials/0_config.md)
-- [add new dataset](docs/en/tutorials/1_new_dataset.md)
-- [data pipeline](docs/en/tutorials/2_data_pipeline.md)
-- [add new module](docs/en/tutorials/3_new_module.md)
-- [customize schedules](docs/en/tutorials/4_schedule.md)
-- [customize runtime](docs/en/tutorials/5_runtime.md)
-- [benchmarks](docs/en/tutorials/6_benchmarks.md)
+MMSelfSup is an open source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks.
+We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new algorithms.
 
-Besides, we provide [colab tutorial](https://github.com/open-mmlab/mmselfsup/blob/master/demo/mmselfsup_colab_tutorial.ipynb) for basic usage.
+MMSelfSup originates from OpenSelfSup, and we appreciate all early contributions made to OpenSelfSup. A few contributors are listed here: Xiaohang Zhan ([@XiaohangZhan](http://github.com/XiaohangZhan)), Jiahao Xie ([@Jiahao000](https://github.com/Jiahao000)), Enze Xie ([@xieenze](https://github.com/xieenze)), Xiangxiang Chu ([@cxxgtxy](https://github.com/cxxgtxy)), Zijian He ([@scnuhealthy](https://github.com/scnuhealthy)).
 
 ## Citation
 
@@ -155,19 +166,9 @@ If you use this toolbox or benchmark in your research, please cite this project.
 }
 ```
 
-## Contributing
-
-We appreciate all contributions improving MMSelfSup. Please refer to [CONTRIBUTING.md](docs/en/community/CONTRIBUTING.md) for more details about the contributing guideline.
-
-## Acknowledgement
-
-Remarks:
+## License
 
-- MMSelfSup originates from OpenSelfSup, and we appreciate all early contributions made to OpenSelfSup. A few contributors are listed here: Xiaohang Zhan, Jiahao Xie, Enze Xie, Xiangxiang Chu, Zijian He.
-- The implementation of MoCo and the detection benchmark borrow the code from [MoCo](https://github.com/facebookresearch/moco).
-- The implementation of SwAV borrows the code from [SwAV](https://github.com/facebookresearch/swav).
-- The SVM benchmark borrows the code from [fair_self_supervision_benchmark](https://github.com/facebookresearch/fair_self_supervision_benchmark).
-- `mmselfsup/utils/clustering.py` is borrowed from [deepcluster](https://github.com/facebookresearch/deepcluster/blob/master/clustering.py).
+This project is released under the [Apache 2.0 license](LICENSE).
 
 ## Projects in OpenMMLab
 

diff --git a/README_zh-CN.md b/README_zh-CN.md
@@ -33,10 +33,14 @@
 
 </div>
 
-## 介绍
+<div align="center">
 
 [English](README.md) | 简体中文
 
+</div>
+
+## 介绍
+
 MMSelfSup 是一个基于 PyTorch 实现的开源自监督表征学习工具箱，是 [OpenMMLab](https://openmmlab.com/) 项目成员之一。
 
 主分支代码支持 **PyTorch 1.5** 及以上的版本。
@@ -59,11 +63,7 @@ MMSelfSup 是一个基于 PyTorch 实现的开源自监督表征学习工具箱
 
   兼容 OpenMMLab 各大算法库，拥有丰富的下游评测任务和预训练模型的应用。
 
-## 开源许可证
-
-该项目采用 [Apache 2.0 开源许可证](LICENSE).
-
-## 更新日志
+## 更新
 
 最新的 **v0.9.0** 版本已经在 2022.04.29 发布。
 
@@ -76,9 +76,31 @@ MMSelfSup 是一个基于 PyTorch 实现的开源自监督表征学习工具箱
 
 MMSelfSup 和 OpenSelfSup 的不同点写在 [对比文档](docs/en/compatibility.md) 中。
 
-## 模型库和基准测试
+## 安装
+
+MMSelfSup 依赖 [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv) 和 [MMClassification](https://github.com/open-mmlab/mmclassification).
+
+请参考 [安装文档](docs/zh_cn/install.md) 获取更详细的安装指南。
+
+## 快速入门
+
+请参考 [准备数据](docs/zh_cn/prepare_data.md) 准备数据集和 [入门指南](docs/zh_cn/get_started.md) 获取 MMSelfSup 的基本使用方法.
+
+我们也提供了更加全面的教程，包括:
+
+- [配置文件](docs/zh_cn/tutorials/0_config.md)
+- [添加数据集](docs/zh_cn/tutorials/1_new_dataset.md)
+- [数据处理流](docs/zh_cn/tutorials/2_data_pipeline.md)
+- [添加新模块](docs/zh_cn/tutorials/3_new_module.md)
+- [自定义流程](docs/zh_cn/tutorials/4_schedule.md)
+- [自定义运行](docs/zh_cn/tutorials/5_runtime.md)
+- [基准测试](docs/zh_cn/tutorials/6_benchmarks.md)
+
+另外，我们提供了 [colab 教程](https://github.com/open-mmlab/mmselfsup/blob/master/demo/mmselfsup_colab_tutorial.ipynb)。
+
+如果遇到问题，请参考 [常见问题解答](docs/zh_cn/faq.md)。
 
-### 模型库
+## 模型库
 
 请参考 [模型库](docs/zh_cn/model_zoo.md) 查看我们更加全面的模型基准结果。
 
@@ -104,7 +126,7 @@ MMSelfSup 和 OpenSelfSup 的不同点写在 [对比文档](docs/en/compatibilit
 
 更多的算法实现已经在我们的计划中。
 
-### 基准测试
+## 基准测试
 
 | 基准测试方法                                             | 参考设置                                                                                                                                                                 |
 | -------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
@@ -120,31 +142,9 @@ MMSelfSup 和 OpenSelfSup 的不同点写在 [对比文档](docs/en/compatibilit
 | Cityscapes Segmentation                            | [MMSeg](configs/benchmarks/mmsegmentation/cityscapes/fcn_r50-d8_769x769_40k_cityscapes.py)                                                                           |
 | PASCAL VOC12 Aug Segmentation                      | [MMSeg](configs/benchmarks/mmsegmentation/voc12aug/fcn_r50-d8_512x512_20k_voc12aug.py)                                                                               |
 
-## 安装
-
-MMSelfSup 依赖 [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv) 和 [MMClassification](https://github.com/open-mmlab/mmclassification).
-
-请参考 [安装文档](docs/zh_cn/install.md) 获取更详细的安装指南。
-
-## 快速入门
-
-请参考 [准备数据](docs/zh_cn/prepare_data.md) 准备数据集和 [入门指南](docs/zh_cn/getting_started.md) 获取 MMSelfSup 的基本使用方法.
-
-我们也提供了更加全面的教程，包括:
-
-- [配置文件](docs/zh_cn/tutorials/0_config.md)
-- [添加数据集](docs/zh_cn/tutorials/1_new_dataset.md)
-- [数据处理流](docs/zh_cn/tutorials/2_data_pipeline.md)
-- [添加新模块](docs/zh_cn/tutorials/3_new_module.md)
-- [自定义流程](docs/zh_cn/tutorials/4_schedule.md)
-- [自定义运行](docs/zh_cn/tutorials/5_runtime.md)
-- [基准测试](docs/zh_cn/tutorials/6_benchmarks.md)
-
-另外，我们提供了 [colab 教程](https://github.com/open-mmlab/mmselfsup/blob/master/demo/mmselfsup_colab_tutorial.ipynb)。
-
 ## 参与贡献
 
-我们非常欢迎任何有助于提升 MMSelfSup 的贡献，请参考 [贡献指南](docs/zh_cn/community/CONTRIBUTING.md) 来了解如何参与贡献。
+我们非常欢迎任何有助于提升 MMSelfSup 的贡献，请参考 [贡献指南](.github/CONTRIBUTING.md) 来了解如何参与贡献。
 
 ## 致谢
 
@@ -165,6 +165,10 @@ MMSelfSup 是一款由不同学校和公司共同贡献的开源项目，我们
 }
 ```
 
+## 开源许可证
+
+该项目采用 [Apache 2.0 开源许可证](LICENSE)。
+
 ## OpenMMLab 的其他项目
 
 - [MMCV](https://github.com/open-mmlab/mmcv): OpenMMLab 计算机视觉基础库

diff --git a/docs/en/community/CONTRIBUTING.md b/docs/en/community/CONTRIBUTING.md
diff --git a/docs/en/getting_started.md → docs/en/get_started.md b/docs/en/getting_started.md → docs/en/get_started.md
diff --git a/docs/en/index.rst b/docs/en/index.rst
@@ -11,7 +11,9 @@ Welcome to MMSelfSup's documentation!
    :caption: Get Started
 
    install.md
-   getting_started.md
+   prepare_data.md
+   get_started.md
+   model_zoo.md
 
 .. toctree::
    :maxdepth: 1
@@ -51,8 +53,8 @@ Welcome to MMSelfSup's documentation!
    :maxdepth: 1
    :caption: Notes
 
-   community/CONTRIBUTING.md
    changelog.md
+   compatibility.md
 
 .. toctree::
    :caption: Switch Language
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1 @@
		We appreciate all contributions to improve MMSelfSup. Please refer to [CONTRIBUTING.md](https://github.com/open-mmlab/mmcv/blob/master/CONTRIBUTING.md) in MMCV for more details about the contributing guideline.