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-0.6.1.dev20200625.tar.gz (84.1 kB view details)

Uploaded Source

Built Distributions

File details

Details for the file mmcv-nightly-0.6.1.dev20200625.tar.gz.

File metadata

  • Download URL: mmcv-nightly-0.6.1.dev20200625.tar.gz
  • Upload date:
  • Size: 84.1 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-0.6.1.dev20200625.tar.gz
Algorithm Hash digest
SHA256 01ddc2e26d31c27ffc19a2f5842434f283147f397c7218ec81312b0f6496f292
MD5 6f2719003797c976986cb9d7bb4e0915
BLAKE2b-256 fa7c7ac6096230694eb47b43ca95f589fd1461e5956eb8ce286dbc1ea7544d2d

See more details on using hashes here.

File details

Details for the file mmcv_nightly-0.6.1.dev20200625-cp38-cp38-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mmcv_nightly-0.6.1.dev20200625-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 b83b91c7cb04e072792d1755ab105357a1909800853959485f9e39138a301c3e
MD5 623be3cf61992c17485b184eed44a4fa
BLAKE2b-256 cc0f8a40f91b8a23679b43cc56143b41254cb20b1d98315d347d4d25007540ad

See more details on using hashes here.

File details

Details for the file mmcv_nightly-0.6.1.dev20200625-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mmcv_nightly-0.6.1.dev20200625-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 ec571188cbfe31aef9126048aaeee02673223f802e1b5225374aa06ebab50b45
MD5 6f16233d2cf8d422abaebe6b488694f2
BLAKE2b-256 9148393d21273dc80b76503f1f66d0a9dd4063ecfdb07db5fbeb1f1df83818f9

See more details on using hashes here.

File details

Details for the file mmcv_nightly-0.6.1.dev20200625-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mmcv_nightly-0.6.1.dev20200625-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 1f45e55f77fec4036631b19a8ce45fc623e1d05bc1f299e60090b4fded67ac18
MD5 843f245871cb769fb4e559d1cbaa7de9
BLAKE2b-256 6e34d5100250a09534673c047d2b021dac1bfb01f9b6bfe16b6a2651745288cc

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