oniazusa

Transform photos into visual-novel backgrounds inspired by Leaf's Kizuato (痕) style.

oniazusa is a standalone CLI for testing the mood, tint, pixel structure, and screen-tone feel of low-resolution, memory-like backgrounds before they are folded into skirts-colour. It is also expected to act as reusable image-processing infrastructure for other tools.

Why oniazusa?

The target is not "anime filter" in the broad web sense. The tool is trying to capture a specific late-90s visual-novel background feeling: reduced detail, tinted paper-like light, and dithered depth instead of photographic realism.

That means the output style matters, but interface stability matters too, because this tool is meant to be called from name-name-based workflows and other repos.

Install

uv tool install oniazusa

Or from source:

git clone https://github.com/kako-jun/oniazusa.git
cd oniazusa
uv sync --group dev
uv run oniazusa --help

Usage

Single image

oniazusa photo.jpg -o background.png

Batch processing

oniazusa ./photos/ -o ./backgrounds/

Change tint and dithering levels

oniazusa photo.jpg --tint green --levels 24 -o background.png

Shape the gradient before the visible grid

oniazusa photo.jpg --pre-blur 1.8 --glow 0.24 -o background.png

Current behavior

• bilateral filtering to flatten texture while preserving edges
• soft edge overlay from Canny outlines
• Gaussian blur plus glow-like smoothing before ordered grid dithering
• heavy downscale then ordered Bayer dithering
• tint mapping through a limited preset palette
• nearest-neighbor upscale for visible dot structure

The CLI is only the first surface. The underlying behavior should remain stable enough for other tools to depend on it.

Limitations

• foreground and background are processed uniformly
• tint presets are still rough and not yet matched against real reference scenes
• there is no --preprocess switch yet for alternate source stylization paths

Docs

• docs/overview.md — artistic target and scope
• docs/spec.md — CLI and filter steps
• docs/roadmap.md — quality gaps and next work
• CLAUDE.md — AI-facing internal guide

Development

uv sync --group dev
uv run ruff check .
uv run pytest