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name: image-testing description: "Run KAIR image restoration inference and evaluation workflows for denoising, deblocking, single-image super-resolution, SwinIR, USRNet, face enhancement, and profiling caveats." metadata: disco-role: operating disable-model-invocation: true license: MIT

KAIR Image Testing

Use this sub-skill when the task is to run, adapt, or debug KAIR image restoration testing/inference workflows: DnCNN/FDnCNN/FFDNet/IRCNN denoising, DnCNN3 deblocking, SRMD/DPSR/MSRResNet/RRDB/IMDN/USRNet image SR, SwinIR image tasks, GPEN face enhancement, model-zoo lookup, or lightweight profiling caveats.

Do not use this sub-skill for training, VRT/RVRT video restoration, or dataset/LMDB preparation. Route those to image-training, video-restoration, or data-preparation respectively.

Operating workflow

1. Identify whether the requested entry point is argparse-based or hard-coded:
   • Use scripts/build_image_test_command.py for dry-run commands for main_test_dncnn.py and main_test_swinir.py.
   • Use references/model-script-reference.md for the distilled model-family to script/checkpoint/data mapping.
   • Use references/image-testing-workflows.md for command patterns, hard-coded-script editing guidance, output locations, metrics, SwinIR task recipes, face enhancement, and profiling caveats.
2. Resolve checkpoint names through the root model-zoo/download guidance before running networked downloads. SwinIR weights live under model_zoo/swinir/; most other image weights live directly under model_zoo/.
3. Before full inference, prefer safe parser checks such as python main_test_dncnn.py --help, python main_test_swinir.py --help, and root downloader --help. Full inference needs local images and checkpoints.
4. For failures, consult references/troubleshooting.md first, especially for missing weights, empty image folders, wrong channel/noise/scale selection, CPU-vs-CUDA behavior, SwinIR tiling, GPEN weights, and the face-enhancer op import-path quirk.

Bundled files

• references/image-testing-workflows.md — practical recipes and editing guidance.
• references/model-script-reference.md — model family, script, checkpoint, and default data-route table.
• references/troubleshooting.md — owned failure modes for image testing.
• scripts/build_image_test_command.py — self-contained dry-run command builder; it imports no KAIR modules and never downloads or runs inference.