From 478563888e73ecd299b479b8eb15e1c0acf95658 Mon Sep 17 00:00:00 2001 From: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com> Date: Sun, 25 Apr 2021 19:25:14 +0800 Subject: [PATCH] [Docs] Refactor readme.md (#984) * [Docs] Refactor readme.md * use lowercase --- README.md | 37 +++++++++++++++++++------------------ README_zh-CN.md | 37 +++++++++++++++++++------------------ 2 files changed, 38 insertions(+), 36 deletions(-) diff --git a/README.md b/README.md index 24f5cb9cd..2180859a1 100644 --- a/README.md +++ b/README.md @@ -11,15 +11,16 @@ English | [简体中文](README_zh-CN.md) 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 -- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): General 3D object detection toolbox and benchmark -- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): Semantic segmentation toolbox and benchmark -- [MMEditing](https://github.com/open-mmlab/mmediting): Image and video editing toolbox -- [MMPose](https://github.com/open-mmlab/mmpose): Pose estimation toolbox and benchmark -- [MMAction2](https://github.com/open-mmlab/mmaction2): Action understanding toolbox and benchmark -- [MMTracking](https://github.com/open-mmlab/mmtracking): Video perception toolbox and benchmark -- [MMClassification](https://github.com/open-mmlab/mmclassification): Image classification toolbox and benchmark -- [MMOCR](https://github.com/open-mmlab/mmocr): A Comprehensive Toolbox for Text Detection, Recognition and Understanding +- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark. +- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark. +- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection. +- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark. +- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark. +- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark. +- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark. +- [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox. +- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition and understanding toolbox. +- [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox. It provides the following functionalities. @@ -39,18 +40,12 @@ Note: MMCV requires Python 3.6+. There are two versions of MMCV: -- **mmcv**: lite, without CUDA ops but all other features, similar to mmcv<1.0.0. It is useful when you do not need those CUDA ops. - **mmcv-full**: comprehensive, with full features and various CUDA ops out of box. It takes longer time to build. +- **mmcv**: lite, without CUDA ops but all other features, similar to mmcv<1.0.0. It is useful when you do not need those CUDA ops. -**Note**: Do not install both versions in the same environment, otherwise you may encounter errors like `ModuleNotFound`. You need to uninstall one before installing the other. +**Note**: Do not install both versions in the same environment, otherwise you may encounter errors like `ModuleNotFound`. You need to uninstall one before installing the other. `Installing the full verion is highly recommended if CUDA is avaliable`. -a. Install the lite version. - -```python -pip install mmcv -``` - -b. Install the full version. +a. Install the full version. Before installing mmcv-full, make sure that PyTorch has been successfully installed following the [official guide](https://pytorch.org/). @@ -167,6 +162,12 @@ pip install mmcv-full Note that the local compiling may take up to 10 mins. +b. Install the lite version. + +```python +pip install mmcv +``` + c. Install full version with custom operators for onnxruntime - Check [here](docs/onnxruntime_op.md) for detailed instruction. diff --git a/README_zh-CN.md b/README_zh-CN.md index 409d09d32..b012af058 100644 --- a/README_zh-CN.md +++ b/README_zh-CN.md @@ -10,15 +10,16 @@ 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： -- [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 -- [MMEditing](https://github.com/open-mmlab/mmediting): 图像视频编辑工具箱 -- [MMPose](https://github.com/open-mmlab/mmpose): 姿态估计工具箱 -- [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 -- [MMClassification](https://github.com/open-mmlab/mmclassification): 图像分类工具箱 -- [MMOCR](https://github.com/open-mmlab/mmocr): 全流程文字检测识别理解工具包 +- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab 图像分类工具箱 +- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab 目标检测工具箱 +- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab 新一代通用 3D 目标检测平台 +- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab 语义分割工具箱 +- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab 新一代视频理解工具箱 +- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab 一体化视频目标感知平台 +- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab 姿态估计工具箱 +- [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab 图像视频编辑工具箱 +- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab 全流程文字检测识别理解工具包 +- [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab 图片视频生成模型工具箱 MMCV 提供了如下众多功能： @@ -38,18 +39,12 @@ MMCV 提供了如下众多功能： 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。 +- **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。 -**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。 +**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。`如果CUDA可用，强烈推荐安装mmcv-full`。 -a. 安装精简版 - -```python -pip install mmcv -``` - -b. 安装完整版 +a. 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/)。 @@ -164,6 +159,12 @@ pip install mmcv-full 但注意本地编译可能会耗时 10 分钟以上。 +b. 安装精简版 + +```python +pip install mmcv +``` + 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)。