Skip to content

Yukaii/ditl

Repository files navigation

ditl

Short for "designer in the loop".

Deterministic pipeline design for turning AI-generated product icon rasters into crisp, reusable SVGs.

This repo starts from a docs-first technical plan. The goal is to make icon vectorization measurable, automatable, and tunable with an AI controller without letting AI directly author final SVG geometry.

Scope

  • Normalize noisy AI-generated icon rasters into traceable flat regions
  • Vectorize with deterministic tools such as VTracer and Potrace
  • Optimize and sanitize SVG output
  • Snap geometry for small-size crispness
  • Validate output with hard gates and a continuous score
  • Use AI only to propose parameter changes between deterministic runs

Docs

Core Principles

  • Deterministic output beats opaque one-shot vector generation
  • Small-size readability at 16, 20, and 24 px is the primary quality bar
  • SVG simplicity matters: fewer paths, fewer nodes, fewer tiny artifacts
  • Acceptance should be based on explicit thresholds and repeatable scoring

Proposed Evaluation Sizes

16, 20, 24, 32, 48, 64, 128, 256

Acceptance Summary

  • Ship: FinalScore >= 86 and all hard gates pass
  • Needs tuning: 78 <= FinalScore < 86
  • Reject: FinalScore < 78

Planned Tooling

  • Raster cleanup and quantization
  • VTracer for multi-color icon tracing
  • Potrace for monochrome silhouettes and logos
  • SVGO for SVG cleanup
  • A scoring runner that renders candidate SVGs back to raster and evaluates them

About

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages