---

name: batch-restoration description: "Run and troubleshoot SUPIR folder-based restoration with test.py-style flags, prompt choices, Q/F checkpoints, CUDA device planning, and safe dry-run validation." metadata: disco-role: operating disable-model-invocation: true license: NOASSERTION

Batch Restoration

Use this sub-skill when the user wants a command-line or scripted folder restoration workflow: input images in a directory, output PNGs in a save directory, SUPIR_sign selection, quality/fidelity flags, manual prompts, --no_llava, or a test.py-style run.

For API-only questions, route to ../python-api-and-config/SKILL.md. For Gradio/browser, tiled local-prompt, or face workflows, route to ../interactive-demos/SKILL.md.

Read these bundled files

• references/workflow-and-cli.md for the adapted batch workflow, options, device assignment, and troubleshooting.
• scripts/supir_batch_restore.py for a safe dry-run wrapper that mirrors the repo batch workflow and only loads models when --run is explicitly passed.
• ../../references/checkpoints-and-environment.md for checkpoint and backend requirements.
• ../../references/configuration-reference.md for shared sampler, dtype, and prompt settings.

Workflow summary

1. Validate CUDA and dependencies with the API probe.
2. Validate checkpoint/config paths with the root asset checker.
3. Choose Q for default high-quality restoration or F for fidelity under light degradation.
4. Choose whether LLaVA captioning is available. Use --no_llava for manual or empty prompts when LLaVA checkpoints are absent.
5. Run a dry run first:

python sub-skills/batch-restoration/scripts/supir_batch_restore.py \
  --img_dir inputs --save_dir outputs --SUPIR_sign Q --upscale 2 --dry-run

6. Only add --run after the dry run shows the intended config, devices, prompts, and output path.

Inputs and outputs

• Input directory: image files readable by Pillow.
• Output directory: created if missing; each input image produces <input_stem>_<sample_index>.png.
• Internal image tensors: RGB, normalized to [-1, 1], working sizes rounded to multiples of 64.
• Captions: generated by LLaVA from a denoised 512-side preview unless --no_llava is used.

Key decisions

Decision	Preferred route
Missing LLaVA or second GPU	Use --no_llava or --load_8bit_llava; provide manual context in prompts when possible.
Large images / memory pressure	Use --use_tile_vae and consider the interactive tiled route for local prompts.
Better visual appeal	Try higher s_cfg, larger spt_linear_CFG, and s_stage2 slightly below 1.0 after validating seed/config.
Better fidelity	Use SUPIR_sign F for light degradation, lower guidance, and s_stage2=1.0.
Reproducibility	Set --seed and record checkpoint variants, prompt suffixes, and color-fix mode.

Guardrails

• The source batch workflow aborts without CUDA. Do not run it on CPU.
• Do not recursively process huge folders without a user-approved budget.
• Do not assume non-image files are safely ignored; validate inputs before long runs.
• Keep checkpoint paths out of public reports.