---

name: metric-usage description: "Routes LPIPS pairwise comparison, directory comparison, spatial maps, and LPIPS-loss optimization workflows." disable-model-invocation: true metadata: disco-role: operating license: BSD 2-Clause

Metric Usage

Use this sub-skill when the request is about comparing images or using LPIPS as a perceptual loss.

Trigger phrases

• "compare these two images"
• "which image is closer"
• "run LPIPS on two folders"
• "show the spatial map"
• "optimize an image with LPIPS"
• "use perceptual loss"

What this route covers

• Single image-pair distance checks.
• Directory-pair comparison on matching filenames.
• All-pairs comparison within one directory.
• LPIPS spatial maps.
• A bounded LPIPS optimization demo.

What this route excludes

• BAPPS 2AFC/JND scoring.
• Dataset download and split management.
• Training and checkpointing.

If the user wants benchmark scoring or training, route to the BAPPS sub-skills instead.

Read these next

• references/workflows.md for the command matrix and safe defaults.
• references/troubleshooting.md for normalization, backend, and plotting issues.
• ../../references/api-reference.md for the verified LPIPS API surface.

Run these helpers

• scripts/compare_images.py for pair, directory-pair, and all-pairs LPIPS comparisons.
• scripts/optimize_lpips.py for a bounded perceptual-loss optimization demo.

The helpers default to the bundled example assets under ../../assets/examples/, so they remain usable even when the original repository checkout is gone.

Working assumptions

• Inputs should be RGB images.
• LPIPS expects tensors scaled to [-1, 1]; the helper scripts handle the conversion for file inputs.
• spatial=True returns a map rather than a single scalar, so use the spatial-map output when you want localization.
• The first LPIPS use may download torchvision backbone weights if they are not cached yet.