Skip to main content

Open MMLab 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 processing

  • Video processing

  • Image and annotation visualization

  • Useful utilities (progress bar, timer, …)

  • PyTorch runner with hooking mechanism

  • Various CNN architectures

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-0.5.9.dev20200615.tar.gz (79.9 kB view details)

Uploaded Source

Built Distributions

File details

Details for the file mmcv-nightly-0.5.9.dev20200615.tar.gz.

File metadata

  • Download URL: mmcv-nightly-0.5.9.dev20200615.tar.gz
  • Upload date:
  • Size: 79.9 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-0.5.9.dev20200615.tar.gz
Algorithm Hash digest
SHA256 15e2ed7d3c7ea66d00896b35b5f69355df9dfe6218c2facf63ce1718b17f1fe8
MD5 e464435cce39bddf070ddac8c45f4577
BLAKE2b-256 ff38292d1a45fb9f0d514e598c3c3b60d62b0ec59daa3ca17470b28fe2e9438f

See more details on using hashes here.

File details

Details for the file mmcv_nightly-0.5.9.dev20200615-cp38-cp38-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mmcv_nightly-0.5.9.dev20200615-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 a1965c5510e48309d23ad8e3cc13d3b9e61fb1ffe67df1cfb7843b6f8211161a
MD5 65179bd5a3b0e88dc1d34856abe873a9
BLAKE2b-256 f678baaa7bc2a947d46fa0c4323ce266fdd507056f1c5f634cbb8c8ca6cb209b

See more details on using hashes here.

File details

Details for the file mmcv_nightly-0.5.9.dev20200615-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mmcv_nightly-0.5.9.dev20200615-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 9e70256e938de0b43269a6ba5ce60eab743ddecbea316578d09f31c219bb1111
MD5 927203051847920654a13d8553ed2e8c
BLAKE2b-256 91d94067424ac907e63990454b054c01dacbab2d7ff88c0366e225517061efc2

See more details on using hashes here.

File details

Details for the file mmcv_nightly-0.5.9.dev20200615-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mmcv_nightly-0.5.9.dev20200615-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 a87d1cc9150934ad516dc36d16f5bb59785f3c51af24927ea81ac911f6e27e7a
MD5 ac4608d866c427ad471a266bd8a72a0c
BLAKE2b-256 50e1e414cb2004d97586d98f5a7767e110e1ac26f3edf6242999816b15ff01aa

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