---

name: data-transforms description: "Compose, customize, inspect, and troubleshoot MMCV dict-style data transform pipelines with mmcv.transforms and MMEngine registries." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

MMCV Data Transforms

Use this sub-skill when a task involves mmcv.transforms, TRANSFORMS, dict-style data pipelines, custom transform registration, transform wrappers, or transform failures involving image/annotation keys.

Read When

• Building a pipeline = [dict(type=...)] list for an OpenMMLab dataset or standalone MMCV preprocessing flow.
• Debugging missing img, img_path, img_shape, ori_shape, pad_shape, scale_factor, flip, gt_bboxes, gt_seg_map, or gt_keypoints keys.
• Writing a custom BaseTransform registered into TRANSFORMS for config-based construction.
• Using Compose, KeyMapper, RandomChoice, RandomApply, TransformBroadcaster, or cached randomness.
• Validating tensor conversion through ToTensor, ImageToTensor, or to_tensor.

Quick Workflow

1. Identify the contract for each transform in references/data-contracts.md before reordering the pipeline.
2. Check constructor defaults and side effects in references/api-reference.md.
3. Start from a recipe in references/workflows.md and adapt keys, shapes, and registry imports deliberately.
4. For failures, match the symptom in references/troubleshooting.md before changing source code.
5. Run scripts/transform_pipeline_check.py --help, then run the checker against a tiny generated fixture to verify key, shape, and type expectations.

Shape Convention Warning

Initialization sizes such as Resize(scale=(width, height)), RandomResize(scale=...), RandomChoiceResize(scales=...), Pad(size=(width, height)), and crop sizes follow width-height argument conventions where documented by MMCV image APIs. Returned metadata keys such as img_shape, ori_shape, and pad_shape are height-width tuples from NumPy image shape.

Boundaries

• Low-level image IO, resizing, padding, normalization, color conversion, and geometric image functions are covered by ../media-processing/.
• CNN layers, model builders, and network initialization are covered by ../cnn-model-building/.
• Compiled ops, CUDA extensions, and full-MMCV build issues are covered by ../ops-and-builds/.

References

• references/api-reference.md for signatures, defaults, registry behavior, and transform side effects.
• references/data-contracts.md for read/write keys, bbox/seg/keypoint shapes, metadata conventions, and tensor assumptions.
• references/workflows.md for pipeline config recipes, custom transform registration, wrappers, and test-time augmentation.
• references/troubleshooting.md for actionable fixes for common transform failures.
• scripts/transform_pipeline_check.py for a self-contained tiny pipeline smoke check.