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customization-extensions

customization-extensions

Customize MMDetection3D datasets, data pipelines, model components, runtime settings, and optional project extensions.

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Documentation de la Skill

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name: customization-extensions description: "Customize MMDetection3D datasets, data pipelines, model components, runtime settings, and optional project extensions." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

customization-extensions

Use this sub-skill when the user needs to add or adapt extension code that must be registered and wired into a config.

Start here

  • references/customization.md for registry, dataset, pipeline, model, and runtime patterns.
  • references/projects.md for optional projects/ packages and compiled extras.
  • references/troubleshooting.md for import, registry, config, and shape pitfalls.
  • scripts/scaffold_custom_component.py to generate a starter tree in a caller-provided output directory.

Typical targets

  • new datasets or dataset subclasses
  • new point or image transforms
  • new backbones, necks, heads, losses, assigners, samplers, or hooks
  • custom optimizers, optimizer constructors, schedulers, or runtime hooks
  • optional project modules that stay outside the core package

Routing rules

  • If the request is mainly config selection or model zoo lookup, route to the configuration sub-skill.
  • If the request is only training, testing, or evaluation command construction, route to the training sub-skill.
  • If the request is raw dataset conversion or info-file generation, route to the data-preparation sub-skill.
  • If the work needs project-specific extras or optional compilation, keep it here and consult references/projects.md.

Operating rule

Prefer custom_imports and generated starter files over editing core package code unless the user explicitly wants an in-tree implementation.

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