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[feature] Add readme of chinese version #846

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add readme of chinese version
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add contribution guide
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12 changes: 9 additions & 3 deletions README.md
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[![PyPI](https://img.shields.io/pypi/v/mmcv)](https://pypi.org/project/mmcv) [![badge](https://github.com/open-mmlab/mmcv/workflows/build/badge.svg)](https://github.com/open-mmlab/mmcv/actions) [![codecov](https://codecov.io/gh/open-mmlab/mmcv/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmcv) [![license](https://img.shields.io/github/license/open-mmlab/mmcv.svg)](https://github.com/open-mmlab/mmcv/blob/master/LICENSE)

English | [简体中文](README_zh-CN.md)

## Introduction

MMCV is a foundational python library for computer vision research and supports many
MMCV is a foundational library for computer vision research and supports many
research projects as below:

- [MMDetection](https://github.com/open-mmlab/mmdetection): Detection toolbox and benchmark
Expand Down Expand Up @@ -146,15 +148,19 @@ Another way is to compile locally by running
pip install mmcv-full
```

Note that the local compiling may take up to 10 mins.

c. Install full version with custom operators for onnxruntime

- Check [here](docs/onnxruntime_op.md) for detailed instruction.

Note that the local compiling may take up to 10 mins.

If you would like to build MMCV from source, please refer to the [guide](https://mmcv.readthedocs.io/en/latest/build.html).

## FAQ

If you face some installation issues, CUDA related issues or RuntimeErrors,
you may first refer to this [Trouble Shooting Page](https://mmcv.readthedocs.io/en/latest/trouble_shooting.html).

## Contributing

We appreciate all contributions to improve MMDetection. Please refer to [CONTRIBUTING.md](CONTRIBUTING.md) for the contributing guideline.
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<div align="center">
<img src="https://raw.githubusercontent.com/open-mmlab/mmcv/master/docs/mmcv-logo.png" width="300"/>
</div>

[![PyPI](https://img.shields.io/pypi/v/mmcv)](https://pypi.org/project/mmcv) [![badge](https://github.com/open-mmlab/mmcv/workflows/build/badge.svg)](https://github.com/open-mmlab/mmcv/actions) [![codecov](https://codecov.io/gh/open-mmlab/mmcv/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmcv) [![license](https://img.shields.io/github/license/open-mmlab/mmcv.svg)](https://github.com/open-mmlab/mmcv/blob/master/LICENSE)

[English](README.md) | 简体中文

## 简介

MMCV 是一个面向计算机视觉的基础库，它支持了很多开源项目，例如：

- [MMCV](https://github.com/open-mmlab/mmcv): 计算机视觉基础库
- [MMClassification](https://github.com/open-mmlab/mmclassification): 图像分类工具箱
- [MMDetection](https://github.com/open-mmlab/mmdetection): 目标检测工具箱
- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): 新一代通用 3D 目标检测平台
- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): 语义分割工具箱
- [MMAction2](https://github.com/open-mmlab/mmaction2): 新一代视频理解工具箱
- [MMTracking](https://github.com/open-mmlab/mmtracking): 一体化视频目标感知平台
- [MMPose](https://github.com/open-mmlab/mmpose): 姿态估计工具箱
- [MMEditing](https://github.com/open-mmlab/mmediting): 图像视频编辑工具箱

MMCV 提供了如下众多功能：

- 通用的 IO 接口
- 图像和视频处理
- 图像和标注结果可视化
- 常用小工具（进度条，计时器等）
- 基于 PyTorch 的通用训练框架
- 多种 CNN 网络结构
- 高质量实现的常见 CUDA 算子

如想了解更多特性和使用，请参考[文档](http://mmcv.readthedocs.io/en/latest)。

提示: MMCV 需要 Python 3.6 以上版本。

## 安装

MMCV 有两个版本：

- **mmcv**: 精简版，不包含 CUDA 算子但包含其余所有特性和功能，类似 MMCV 1.0 之前的版本。如果你不需要使用 CUDA 算子的话，精简版可以作为一个考虑选项。
- **mmcv-full**: 完整版，包含所有的特性以及丰富的开箱即用的 CUDA 算子。注意完整版本可能需要更长时间来编译。

**注意**: 请不要在同一个环境中安装两个版本，否则可能会遇到类似 `ModuleNotFound` 的错误。在安装一个版本之前，需要先卸载另一个。

a. 安装精简版

```python
pip install mmcv
```

b. 安装完整版

在安装 mmcv-full 之前，请确保 PyTorch 已经成功安装在环境中，可以参考 PyTorch 官方[文档](https://pytorch.org/)。

我们提供了不同 PyTorch 和 CUDA 版本的 mmcv-full 预编译包，可以大大简化用户安装编译过程。强烈推荐通过预编译包来安装。

i. 安装最新版本

如下是安装最新版 ``mmcv-full`` 的命令

```shell
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html
```

请将链接中的 ``{cu_version}`` 和 ``{torch_version}`` 根据自身需求替换成实际的版本号，例如想安装和 ``CUDA 11``、``PyTorch 1.7.0`` 兼容的最新版 ``mmcv-full``，使用如下替换过的命令

```shell
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.0/index.html
```

如果想知道更多 CUDA 和 PyTorch 版本的命令，可以参考下面的表格，将链接中的 ``=={mmcv_version}`` 删去即可。

ii. 安装特定的版本

如下是安装特定版本 ``mmcv-full`` 的命令

```shell
pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html
```

首先请参考版本发布信息找到想要安装的版本号，将 ``{mmcv_version}`` 替换成该版本号，例如 ``1.2.2``。
然后将链接中的 ``{cu_version}`` 和 ``{torch_version}`` 根据自身需求替换成实际的版本号，例如想安装和 ``CUDA 11``、``PyTorch 1.7.0`` 兼容的 ``mmcv-full`` 1.2.2 版本，使用如下替换过的命令

```shell
pip install mmcv-full==1.2.2 -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.0/index.html
```

对于更多的 PyTorch 和 CUDA 版本组合，请参考下表：

<table class="docutils">
<tbody>
<tr>
<th width="80"> CUDA </th>
<th valign="bottom" align="left" width="100">torch 1.7</th>
<th valign="bottom" align="left" width="100">torch 1.6</th>
<th valign="bottom" align="left" width="100">torch 1.5</th>
<th valign="bottom" align="left" width="100">torch 1.4</th>
<th valign="bottom" align="left" width="100">torch 1.3</th>
</tr>
<tr>
<td align="left">11.0</td>
<td align="left"><details><summary> 安装 </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.0/index.html</code></pre> </details> </td>
<td align="left"> </td>
<td align="left"> </td>
<td align="left"> </td>
<td align="left"> </td>
</tr>
<tr>
<td align="left">10.2</td>
<td align="left"><details><summary> 安装 </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.7.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.6.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.5.0/index.html</code></pre> </details> </td>
<td align="left"> </td>
<td align="left"> </td>
</tr>
<tr>
<td align="left">10.1</td>
<td align="left"><details><summary> 安装 </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.7.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.5.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.4.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.3.0/index.html</code></pre> </details> </td>
</tr>
<tr>
<td align="left">9.2</td>
<td align="left"><details><summary> 安装 </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu92/torch1.7.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu92/torch1.6.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu92/torch1.5.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu92/torch1.4.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu92/torch1.3.0/index.html</code></pre> </details> </td>
</tr>
<tr>
<td align="left">cpu</td>
<td align="left"><details><summary> 安装 </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.7.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.6.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.5.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.4.0/index.html</code></pre> </details> </td>
<td align="left"><details><summary> 安装 </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.3.0/index.html</code></pre> </details> </td>
</tr>
</tbody>
</table>

除了使用预编译包之外，另一种方式是在本地进行编译，直接运行下述命令

```python
pip install mmcv-full
```

但注意本地编译可能会耗时 10 分钟以上。

c. 安装完整版并且编译 onnxruntime 的自定义算子

- 详细的指南请查看 [这里](docs/onnxruntime_op.md)。

如果想从源码编译 MMCV，请参考[该文档](https://mmcv.readthedocs.io/en/latest/build.html)。

## FAQ
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如果你遇到了安装问题，CUDA 相关的问题或者 RuntimeErrors，可以首先参考[问题解决页面](https://mmcv.readthedocs.io/en/latest/trouble_shooting.html) 看是否已经有解决方案。

## 贡献指南

我们感谢所有的贡献者为改进和提升 MMCV 所作出的努力。请参考[贡献指南](CONTRIBUTING.md)来了解参与项目贡献的相关指引。