# mmcv **Repository Path**: petissue/mmcv ## Basic Information - **Project Name**: mmcv - **Description**: 面向计算机视觉的基础库,支持 Linux、Windows 以及 MacOS 平台。它提供了众多功能,包括基于 PyTorch 的通用训练框架、高质量实现的常见 CUDA 算子、通用的 IO 接口、图像和视频处理、图像和标注结果可视化、多种 CNN 网络结构等功能、常用小工具(进度条,计时器等)。 - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 22 - **Created**: 2022-08-05 - **Last Updated**: 2023-12-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README
[](https://mmcv.readthedocs.io/en/latest/) [](https://pypi.org/project/mmcv/) [](https://pypi.org/project/mmcv) [](https://github.com/open-mmlab/mmcv/actions) [](https://codecov.io/gh/open-mmlab/mmcv) [](https://github.com/open-mmlab/mmcv/blob/master/LICENSE) English | [简体中文](README_zh-CN.md) ## Introduction MMCV is a foundational library for computer vision research and supports many research projects as below: - [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages. - [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. - [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark. - [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark. - [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox. - [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark. - [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark. - [MMSelfSup](https://github.com/open-mmlab/mmselfsup): OpenMMLab self-supervised learning toolbox and benchmark. - [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab model compression toolbox and benchmark. - [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning 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. - [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark. - [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox. - [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox. - [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab model deployment framework. 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 It supports the following systems. - Linux - Windows - macOS See the [documentation](http://mmcv.readthedocs.io/en/latest) for more features and usage. Note: MMCV requires Python 3.6+. ## Installation There are two versions of MMCV: - **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. `Installing the full version is highly recommended if CUDA is available`. a. Install the full version. Before installing mmcv-full, make sure that PyTorch has been successfully installed following the [official guide](https://pytorch.org/). We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA versions to simplify the building for **Linux and Windows systems**. In addition, you can run [check_installation.py](.dev_scripts/check_installation.py) to check the installation of mmcv-full after running the installation commands. i. Install the latest version. The rule for installing the latest `mmcv-full` is as follows: ```shell pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html ``` Please replace `{cu_version}` and `{torch_version}` in the url to your desired one. For example, to install the latest `mmcv-full` with `CUDA 11.1` and `PyTorch 1.9.0`, use the following command: ```shell pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html ``` **Note**: mmcv-full is only compiled on PyTorch 1.x.0 because the compatibility usually holds between 1.x.0 and 1.x.1. If your PyTorch version is 1.x.1, you can install mmcv-full compiled with PyTorch 1.x.0 and it usually works well. For example, if your PyTorch version is 1.8.1 and CUDA version is 11.1, you can use the following command to install mmcv-full. ```shell pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.8.0/index.html ``` For more details, please refer the the following tables and delete `=={mmcv_version}`. ii. Install a specified version. The rule for installing a specified `mmcv-full` is as follows: ```shell pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html ``` First of all, please refer to the Releases and replace `{mmcv_version}` a specified one. e.g. `1.3.9`. Then replace `{cu_version}` and `{torch_version}` in the url to your desired versions. For example, to install `mmcv-full==1.3.9` with `CUDA 11.1` and `PyTorch 1.9.0`, use the following command: ```shell pip install mmcv-full==1.3.9 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html ``` For more details, please refer the the following tables.| CUDA | torch 1.11 | torch 1.10 | torch 1.9 | torch 1.8 | torch 1.7 | torch 1.6 | torch 1.5 |
|---|---|---|---|---|---|---|---|
| 11.5 | install |
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| 11.3 | install |
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| 11.1 | install |
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| 11.0 | install |
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| 10.2 | install |
install |
install |
install |
install |
install |
install |
| 10.1 | install |
install |
install |
install |
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| 9.2 | install |
install |
install |
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| cpu | install |
install |
install |
install |
install |
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install |