Author here. A few notes on how it works.
The interesting part is the colour matching. Naive RGB nearest-neighbour looks bad on skin tones and gradients — you get muddy patches. Two passes works much better: map every pixel to the nearest colour in the actual brand palette using CIEDE2000 perceptual distance, then reduce that set by frequency down to the target colour count, then dither against the reduced palette. Matching against the real palette before reduction is what keeps gradients from collapsing.
Background removal combines the alpha channel with a multi-edge flood fill, with a sanity cap so it doesn't eat the subject when foreground and background are close in tone.
It all runs client-side in a Web Worker — no image leaves the browser, and no account is needed to generate a pattern. Static site on Cloudflare Workers.
The palette data took the longest: 1,406 entries across Perler / Hama / Artkal / MARD / COCO. Every brand numbers its colours differently and none of them publish anything machine-readable.
It also self-hosts Fusion Pixel 12 for CJK pixel typography, which meant building a font-slicing pipeline — a full CJK pixel font is far too heavy to ship whole.
Happy to answer questions.
Our products: Essay Sloth (http://essaysloth.com) and ChatPaper (http://chatpaper.ai).
Company website: https://pomodiary.com/