技能创建器
skill-creator
创建、改进和评估自定义技能,把专业流程转化为可重复使用的 AI 能力。
datasets-and-preprocessing【数据与研究】Route Det3D dataset layout, metadata conversion, annotation, loading, voxelization, and pipeline-preprocessing tasks.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this route for KITTI, nuScenes, or Lyft directory layouts; info/database creation; annotation schemas; point-cloud loading; voxel/pillar preprocessing; transforms; and dataset validation. Read data-formats.md before changing a config and data-preparation.md before running a conversion.
scripts/validate_dataset_layout.py as a non-mutating preflight.create_data or training/evaluation; conversion can write
many files and may require dataset SDKs and a GPU environment.Dataset conversion, ground-truth database creation, and full loaders are not validated by an empty directory or a config parse. Keep data and output paths user-supplied; never embed checkout-specific paths in reusable instructions.
For model/config coupling use configuration-and-models; for CLI execution use
training-and-evaluation; for missing SDKs or compiled ops use runtime-ops.