---

name: mmcv description: "Use MMCV 2.2.0 for computer-vision media utilities, transform pipelines, CNN builders, and compiled ops installation or troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

MMCV Repo Skill

Use this repo skill when a task names MMCV, OpenMMLab computer-vision utilities, mmcv, mmcv-lite, mmcv.transforms, mmcv.cnn, mmcv.ops, image/video/flow helpers, transform pipelines, CNN layer builders, or MMCV install/build failures.

Start Here

1. Identify whether the task is a pure Python utility workflow, a PyTorch model-building workflow, or a compiled ops/build workflow.
2. If the task involves package selection, _ext, CUDA, native kernels, or mmcv.ops, route to sub-skills/ops-and-builds/ before writing code.
3. If the task is media preprocessing or visualization, route to sub-skills/media-processing/.
4. If the task is a dict-style data pipeline or registry transform, route to sub-skills/data-transforms/.
5. If the task is a PyTorch CNN layer/module builder, route to sub-skills/cnn-model-building/.
6. Check references/repo-provenance.md before deciding whether this skill is current for a repository checkout.

Install And Import Baseline

MMCV 2.x has two package variants:

• mmcv-lite imports as mmcv and covers Python/Numpy/MMEngine/PyTorch utility surfaces that do not need compiled mmcv._ext ops.
• mmcv is the full package variant for compiled ops. Use it when code imports mmcv.ops or needs native CPU/CUDA/backend kernels.
• Do not install both variants in the same environment. If switching, uninstall the other variant first.

Minimal import check for lite-safe workflows:

python - <<'PY'
import mmcv
print(mmcv.__version__)
PY

For full ops workflows, use sub-skills/ops-and-builds/scripts/check_mmcv_install.py with --require-ops.

Sub-Skill Routes

Route	Use When	Start With
sub-skills/media-processing/	Image IO, color conversions, resize/crop/pad/rotate/flip, normalization, video reader/editing helpers, optical flow, visualization, array quantization.	sub-skills/media-processing/SKILL.md
sub-skills/data-transforms/	mmcv.transforms, Compose, LoadImageFromFile, Resize, Pad, Normalize, custom BaseTransform, transform wrappers, dict-key/shape failures.	sub-skills/data-transforms/SKILL.md
sub-skills/cnn-model-building/	mmcv.cnn builders, ConvModule, depthwise separable modules, wrappers, plugin layers, fusion, model complexity, CPU-safe PyTorch blocks.	sub-skills/cnn-model-building/SKILL.md
sub-skills/ops-and-builds/	mmcv vs mmcv-lite, MIM/pip/source builds, CUDA/PyTorch compatibility, mmcv.ops, _ext import failures, native extension diagnostics.	sub-skills/ops-and-builds/SKILL.md

Shared References And Scripts

• references/troubleshooting.md covers cross-cutting package, import, routing, optional dependency, and version issues.
• references/repo-provenance.md records the source snapshot used to generate this skill and when to refresh it.
• references/repo-routing-metadata.json is structured metadata used by the managed repo-skills-router import process.
• scripts/check_mmcv_environment.py runs every bundled helper that is safe for the currently installed package variant and summarizes the result.

Routing Pitfalls

• import mmcv succeeding does not prove mmcv.ops is available.
• Most media and transform workflows are lite-safe, but video editing may need external codec support and tensor formatting may need PyTorch.
• mmcv.cnn is PyTorch-dependent, but many builders do not require compiled MMCV ops.
• Size arguments often use width-height order, while NumPy metadata usually reports height-width shape.
• Headless agents should prefer file outputs or returned arrays instead of GUI display helpers.