Visual Pipeline

한국어 버전

This document shows where the OpenToonz-inspired line tools fit in the current rough-sketch-to-color research pipeline.

Research Position

flowchart TD
    A[Blue manuscript page] --> B[Mr.Blue YOLO-seg panel detector]
    B --> C[Polygon-masked panel crops]
    C --> D{Preprocess?}
    D -->|baseline| E[Raw crop to Qwen Image Edit]
    D -->|OT-inspired| F[Blue Line Cleanup]
    F --> G[Line AutoClose]
    G --> H[Region Palette Map]
    H --> I[Qwen Image Edit or MangaNinja]
    E --> J[Colored panel]
    I --> J
    J --> K[Panel Reassemble]

Node Chain

flowchart LR
    A[Load Image / Panel Crop] --> B[OT Blue Line Cleanup]
    B --> C[OT Line AutoClose]
    C --> D[OT Region Palette Map]
    D --> E[Colorization Node]
    E --> F[Reassemble]

Output Artifacts

flowchart TD
    A[OT Blue Line Cleanup] --> A1[clean_line IMAGE]
    A --> A2[line_overlay IMAGE]
    A --> A3[settings_json]
    B[OT Line AutoClose] --> B1[closed_line IMAGE]
    B --> B2[closure_overlay IMAGE]
    B --> B3[segments_json]
    C[OT Region Palette Map] --> C1[region_preview IMAGE]
    C --> C2[regions_json]

Experiment Matrix

Variant	Input to color model	Expected benefit	Risk
A	raw panel crop	fastest baseline	blue rough may leak into output
B	clean line crop	less blue noise	may remove useful semantic detail
C	clean line + autoclose	better fill stability	gap closure may create false lines
D	clean line + autoclose + region JSON	easier post-correction	needs downstream region-aware tooling

Adoption Gate

Use these tools as a default only if they improve at least one measurable outcome:

fewer blue artifacts in final output,
fewer color leaks across line boundaries,
better character/costume color consistency after correction,
easier manual review because overlays/JSON explain preprocessing choices.

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