Iterative image reconstruction using random cubic bézier strokes

Summary

splined# iterative image reconstruction using random cubic bézier strokes, accelerated on metal showcase# NOTE images used here are all under open access by The Met same input & different seeds → different reconstructions → simple animation: build# cargo build -r usage# splined: iterative image reconstruction with random cubic bézier strokes (metal-accelerated) usage: splined <input> [args] args: -n, --number <u32> max splines to draw (default: (w*h)^0.7) -b, --batch <u32> batch size per gpu step (default: 32) -s, --seed <u64> rng seed (default: 0) --max-gpu <f32> max gpu usage in (0, 1] (default: 1.0) -l, --log <0..3> logging level (default: 1) -o, --output <path> output file or dir (default: output.png) -c, --current <path> current canvas image to resume from (single-file only) --nth <u32> save every nth accepted stroke (uses -o as dir) --bg <avg|r,g,b> initial canvas color (default: avg) -a, --alpha <f32> stroke alpha in [0, 1] (default: 1) --min-accept-ratio <f32> stagnant if accepted < batch*ratio (default: 0.02) --max-stagnant-batches <u32> stop after this many stagnant batches (default: 10) input: - file: writes one image to -o/--output (default: output.png) - dir: -o/--output must be a dir; mirrors input tree under it - --nth: saves frames to output dir every nth accepted stroke; also writes final.png examples: splined in.png -o out.png splined in.png -n 5000 -b 64 -s 42 -o out.png splined in.png --nth 50 -o frames/ splined images/ -o results/ -n 5000 -b 64 -s 42 --nth 50 algorithm# convert input to oklab color space initialize canvas to image average (or --bg) repeat until target stroke count or convergence: sample batch of random cubic béziers (4 control points, uniform over image) rasterize each curve to coverage mask set stroke color to coverage-weighted mean of target pixels accept curves that strictly reduce squared oklab error (Δε² < 0) commit accepted strokes to canvas export final canvas reference# Geometrize: a desktop app that geometrizes images i...