Agent skill · creative production · aradotso
see-through-anime-layer-decomposition
Expertise in See-through, a framework for single-image layer decomposition of anime characters into manipulatable 2.5D PSD files using diffusion models.
Why this skill is useful
Adds executable scripts for decomposing anime images into layered PSD files, which the AI cannot generate from existing knowledge.
What it needs
Requires conda, torch installed locally. About 5k tokens when loaded. Last updated 2026-07-09. 70 stars on the source repository.
What this skill does
See-through: Anime Character Layer Decomposition Skill by ara.so — Daily 2026 Skills collection. See-through is a research framework (SIGGRAPH 2026, conditionally accepted) that decomposes a single anime illustration into up to 23 fully inpainted, semantically distinct layers with inferred drawing orders — exporting a layered PSD file suitable for 2.5D animation workflows. What It Does Decomposes a single anime image into semantic layers (hair, face, eyes, clothing, accessories, etc.) Inpaints occluded regions so each layer is complete Infers pseudo-depth ordering using a fine-tuned Marigold model Exports layered .psd files with depth maps and segmentation masks Supports depth-based and left-right stratification for further refinement Installation Optional Annotator Tiers Install only what you need: Always run all scripts from the repository root as the working directory. Models Models are hosted on HuggingFace and downloaded automatically on first use: Model HuggingFace ID Purpose ------- --------------- --------- LayerDiff 3D layerdifforg/seethroughv0.0.2layerdiff3d SDXL-based transparent layer generation Marigold Depth 24yearsold/seethroughv0.0.1marigold Anime pseudo-depth estimation SAM Body Parsing 24yearsold/l2dsamiter2 19-part semantic body segmentation Key CLI Commands Main Pipeline: Layer Decomposition to PSD Output is saved to workspace/layerdiffoutput/ by default. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/see-through-anime-layer-decomposition