# open-mmlab/mmcv

OpenMMLab Computer Vision Foundation

Repository: https://github.com/open-mmlab/mmcv
Canonical: https://ross.abutalabs.com/products/mmcv
Homepage: https://mmcv.readthedocs.io/en/latest/
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2026-01-29T17:08:43+00:00

## Health v2 (maintenance only)
Score: 52/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 64, release rhythm 8, longevity 100
- inputs: {"age_days": 2933, "days_push": 216, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6470, forks 1771 (observed 2026-08-28T04:09:43.680168+00:00)

## What it is
MMCV is the foundational computer vision library for the OpenMMLab ecosystem, providing image/video I/O, data transformations, and CUDA operators built on PyTorch. It serves as the base dependency for OpenMMLab projects like MMDetection and MMSegmentation.

## Use cases
- build computer vision models on pytorch
- image and video io and preprocessing
- run cuda ops for detection models
- data augmentation transforms for vision training
- foundation library for mmdetection and mmsegmentation

## When to choose
- you use OpenMMLab toolboxes like MMDetection, MMSegmentation, or MMPose
- you need optimized CUDA vision operators with PyTorch
- you want a shared set of image/video transforms and I/O utilities

## When to avoid
- you need a full training engine - use MMEngine instead
- you want a standalone high-level vision framework rather than a foundation library
- you don't use PyTorch

## Facets
- artifact type: library
- maturity: stable
- function: image-processing, machine-learning, deep-learning, data-visualization
- domain: computer-vision, deep-learning, machine-learning
- platform: windows, python
- tags: pytorch, opencv, computer-vision-foundation, openmmlab, data-transformations, cuda-ops, linux, macos, gpu, cuda

## Member repositories
- open-mmlab/mmcv (main) score 52

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:43.680168+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:44:35.961927+00:00, confidence not recorded.
  - readme: https://github.com/open-mmlab/mmcv (fetched 2026-08-28T04:09:43.680168+00:00, sha 1c99d2429ba6)
  - registry_pypi: https://pypi.org/pypi/mmcv/json (fetched 2026-08-29T08:41:42.849954+00:00, sha e571c8d41a51)
- Data as of 2026-08-30T08:39:29.467469+00:00.