# Visual Pipeline [한국어 버전](visual_pipeline.ko.md) This document shows where the OpenToonz-inspired line tools fit in the current rough-sketch-to-color research pipeline. ## Research Position ```mermaid 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 Sketch Cleaner] F --> G[Line Gap Closer] G --> H[Color Region Finder] H --> I[Qwen Image Edit or MangaNinja] E --> J[Colored panel] I --> J J --> K[Panel Reassemble] ``` ## Node Chain ```mermaid flowchart LR A[Load Image / Panel Crop] --> B[Blue Sketch Cleaner] B --> C[Line Gap Closer] C --> D[Color Region Finder] D --> E[Colorization Node] E --> F[Reassemble] ``` ## Output Artifacts ```mermaid flowchart TD A[Blue Sketch Cleaner] --> A1[clean_line IMAGE] A --> A2[line_overlay IMAGE] A --> A3[settings_json] B[Line Gap Closer] --> B1[closed_line IMAGE] B --> B2[closure_overlay IMAGE] B --> B3[segments_json] C[Color Region Finder] --> 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 | Current local comparison: - [Panel Colorization Comparison](experiments/colorization_comparison.md) - On local Apple Silicon, `clean_line` / `closed_line` helps remove blue rough artifacts before img2img. - The available SD1.5 ControlNet workflow is too generative for faithful panel preservation. - The installed fp8 Qwen Image Edit model should be retried on CUDA because MPS does not support the required float8 path. ## 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.