Palette-quantize generated brand PNGs#25
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Palette-quantize generated PNGs (Pillow FASTOCTREE) in raster.py — ~70-80% smaller, visually lossless for flat art, alpha preserved on transparent marks. SVGs and external optimizers out of scope. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Two tasks: add Pillow + the FASTOCTREE quantize step in raster.py (with tests and regenerated PNGs), then docs/finalize. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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What
Folds a palette-quantization pass into the brand build so every generated PNG is committed in compact indexed-colour form. The art is flat 2–3 colour, so quantizing
rsvg-convert's 32-bit RGBA output to a palette is visually lossless and cuts the large assets ~70–80%:mark-1024~25–36 KB → ~8 KBDone with Pillow (
Image.Quantize.FASTOCTREE, 32-colour palette) inbrand/build/raster.py::_quantize_png, called at the end ofexport_png— no Node, no required system binary. FASTOCTREE preserves alpha, so transparent marks keep clean edges (verified on light/dark). SVGs are deliberately untouched.Design
planning/changes/2026-06-30.03-png-optimization/design.mdplan.mdNotes
tests/test_pngopt.py) assert indexed mode, dimensions, transparency on the marks, size ceilings, and palette reduction; output is pristine. 91 tests pass;just check-planningOK.pngquant/oxipng), the 1280×640-vs-1200×630 ratio, and re-copying the smaller cards into the 7 docs-repo PRs (a follow-up).🤖 Generated with Claude Code