Skip to main content

OpenMMLab Computer Vision Foundation

Project description

https://img.shields.io/pypi/v/mmcv https://github.com/open-mmlab/mmcv/workflows/build/badge.svg https://codecov.io/gh/open-mmlab/mmcv/branch/master/graph/badge.svg https://img.shields.io/github/license/open-mmlab/mmcv.svg

Introduction

MMCV is a foundational python library for computer vision research and supports many research projects in MMLAB, such as MMDetection and MMAction.

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

Try and start with

pip install mmcv

or install from source

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

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mmcv-nightly-1.0rc0.dev20200628.tar.gz (161.5 kB view details)

Uploaded Source

Built Distributions

File details

Details for the file mmcv-nightly-1.0rc0.dev20200628.tar.gz.

File metadata

  • Download URL: mmcv-nightly-1.0rc0.dev20200628.tar.gz
  • Upload date:
  • Size: 161.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.6.8

File hashes

Hashes for mmcv-nightly-1.0rc0.dev20200628.tar.gz
Algorithm Hash digest
SHA256 6cc882d952d3254631a27dffa5e94f95fc64bb6b448587035b8473ac7ec1e518
MD5 2205c6c3997d3d7a85668b3574b460b6
BLAKE2b-256 729e3b055977e116ea497dd486c1e0c1d37b8ed7d802b3f64d649192a448fce4

See more details on using hashes here.

File details

Details for the file mmcv_nightly-1.0rc0.dev20200628-cp38-cp38-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mmcv_nightly-1.0rc0.dev20200628-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 ce2e2c7d24b80914b780fa7367ea3fdbd8c97cc1f3eb32ecfe4aa20080efe097
MD5 e733748f95659d9de60fe35628023675
BLAKE2b-256 932bcdf32de6d1015eee93cafbac9dda4e2978dc513a371bc61e134b4a77b51c

See more details on using hashes here.

File details

Details for the file mmcv_nightly-1.0rc0.dev20200628-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mmcv_nightly-1.0rc0.dev20200628-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 2b65695d4c691ae660008118172efb3f8c8a24805d869b57e5a84919f9043413
MD5 fb8d0883cefe4c06b5f7fb83b1958898
BLAKE2b-256 4c1d430f60dc4590f399e3e277a5b0aa4a267283729cbc3660cd13fef4350379

See more details on using hashes here.

File details

Details for the file mmcv_nightly-1.0rc0.dev20200628-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mmcv_nightly-1.0rc0.dev20200628-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 21ab2bcb7d9756dc0134eca13a3bdeea8c55d4cd4221ae40b73c358ca1d7db3b
MD5 93f8ee933ce9dbe6bac8332680cce584
BLAKE2b-256 0e0640efe78f8e25d0cacbfe357e3859f079309035873576899cf9c07de9f596

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page