Introduction

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

• MMDetection: Detection toolbox and benchmark
• MMDetection3D: General 3D object detection toolbox and benchmark
• MMSegmentation: Semantic segmentation toolbox and benchmark
• MMEditing: Image and video editing toolbox
• MMPose: Pose estimation toolbox and benchmark
• MMAction2: Action understanding toolbox and benchmark
• MMClassification: Image classification toolbox and benchmark

It provides the following functionalities.

• Universal IO APIs
• Image/Video processing
• Image and annotation visualization
• Useful utilities (progress bar, timer, ...)
• PyTorch runner with hooking mechanism
• Various CNN architectures
• High-quality implementation of common CUDA ops

See the documentation for more features and usage.

Note: MMCV requires Python 3.6+.

Installation

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.

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.

Install with pip

a. Install the lite version.

pip install mmcv

b. Install the full version.

Before installing mmcv-full, make sure that PyTorch has been successfully installed following the official guide.

We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA versions to simplify the building.

CUDA	torch 1.5	torch 1.4	torch 1.3
10.2	install pip install mmcv-full==latest+torch1.5.0+cu102 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
10.1	install pip install mmcv-full==latest+torch1.5.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html	install pip install mmcv-full==latest+torch1.4.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html	install pip install mmcv-full==latest+torch1.3.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
10.0
9.2	install pip install mmcv-full==latest+torch1.5.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html	install pip install mmcv-full==latest+torch1.4.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html	install pip install mmcv-full==latest+torch1.3.0+cu92 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
cpu	install pip install mmcv-full==latest+torch1.5.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html	install pip install mmcv-full==latest+torch1.4.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html	install pip install mmcv-full==latest+torch1.3.0+cpu -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html

Another way is to compile locally by running

pip install mmcv-full

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

Install from source

After cloning the repo with

git clone https://github.com/open-mmlab/mmcv.git
cd mmcv

You can either

• install the lite version

  pip install -e .
  

• install the full version

  MMCV_WITH_OPS=1 pip install -e .
  

If you are on macOS, add the following environment variables before the installing command.

CC=lang CXX=clang++ CFLAGS='-stdlib=libc++'

e.g.,

CC=lang CXX=clang++ CFLAGS='-stdlib=libc++' MMCV_WITH_OPS=1 pip install -e .

Note: If you would like to use opencv-python-headless instead of opencv-python, e.g., in a minimum container environment or servers without GUI, you can first install it before installing MMCV to skip the installation of opencv-python.