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开发与工程 · SKILL.md

video-restoration

video-restoration

【开发与工程】KAIR VRT and RVRT video restoration testing and training guidance for video super-resolution, deblurring, denoising, frame interpolation, and space-time SR.

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技能说明

GitHub

name: video-restoration description: "KAIR VRT and RVRT video restoration testing and training guidance for video super-resolution, deblurring, denoising, frame interpolation, and space-time SR." metadata: disco-role: operating disable-model-invocation: true license: MIT

KAIR video restoration router

Use this sub-skill when the task is about KAIR VRT or RVRT video workflows: video super-resolution, video deblurring, video denoising, video frame interpolation, space-time video SR, VRT/RVRT task IDs, video tiling/OOM, VRT or RVRT training configs, or RVRT custom CUDA extension failures.

Before giving commands, assume the user is in their own KAIR checkout and has installed PyTorch plus KAIR's requirement.txt dependencies. Treat VRT/RVRT full inference and training as CUDA-first workflows; RVRT's guided deformable attention path requires a working CUDA-capable PyTorch build, nvcc, and ninja for the custom extension.

Read these bundled references

  • references/vrt-rvrt-task-reference.md for the VRT 001-009 and RVRT 001-006 task namespaces, checkpoint names, default test folders, and training config paths.
  • references/video-restoration-workflows.md for quick testing, custom-folder commands, training command patterns, data layout expectations, tile semantics, auto-download caveats, and metric/output behavior.
  • references/troubleshooting.md when CUDA extension builds, missing weights, missing data, Vimeo preparation, DDP checkpoint/static-graph resumes, num_workers, or OOM are involved.
  • scripts/build_video_restoration_command.py to print safe KAIR VRT/RVRT test commands without importing KAIR, downloading files, or launching inference.

Route to siblings for non-owned work

  • Route video dataset regrouping, LMDB creation, meta-info validation, and destructive preparation scripts to ../data-preparation/SKILL.md.
  • Route generic image restoration testing to ../image-testing/SKILL.md.
  • Route generic image training and non-video KAIR configs to ../image-training/SKILL.md.
  • Route shared checkpoint acquisition policy to the root model-zoo/download guidance when available; VRT/RVRT test scripts can auto-download missing weights and some testsets, so call that out before running them.

Do not ask future agents to inspect the original KAIR source or docs for these workflows. The operational task tables, command patterns, caveats, and failure modes are distilled into this sub-skill's bundled references.

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