// Upscale a pose layer smoothly, then snap every pixel to the pose's own k main colours so the tracer sees flat regions.
// Soft (WhatsApp/JPEG) outlines otherwise trace as many thin shade-strips that vtracer drops as speckles.
// The palette comes from the pose itself (k-means), never from the brand palette: see companion.md on quantising.
const sharp = require("module").createRequire("/home/ubuntu/kalki-cli/projects/mybazaar-web/package.json")("sharp");
const [, , input, output, kArg = "8", scaleArg = "4"] = process.argv;
const k = +kArg, scale = +scaleArg;
(async () => {
	const meta = await sharp(input).metadata();
	const { data, info } = await sharp(input).ensureAlpha()
		.resize(meta.width * scale, meta.height * scale, { kernel: "lanczos3" })
		.raw().toBuffer({ resolveWithObject: true });
	const n = info.width * info.height;
	const samples = [];
	for (let p = 0; p < n; p += 7) if (data[p * 4 + 3] > 200) samples.push([data[p * 4], data[p * 4 + 1], data[p * 4 + 2]]);
	// k-means++ style seeding by spreading over the sample, then 15 Lloyd iterations.
	let centres = [samples[0]];
	while (centres.length < k) {
		let best = null, bestD = -1;
		for (let s = 0; s < samples.length; s += 13) {
			const d = Math.min(...centres.map((c) => (c[0] - samples[s][0]) ** 2 + (c[1] - samples[s][1]) ** 2 + (c[2] - samples[s][2]) ** 2));
			if (d > bestD) { bestD = d; best = samples[s]; }
		}
		centres.push(best);
	}
	const nearest = (r, g, b) => { let bi = 0, bd = Infinity; centres.forEach((c, i) => { const d = (c[0] - r) ** 2 + (c[1] - g) ** 2 + (c[2] - b) ** 2; if (d < bd) { bd = d; bi = i; } }); return bi; };
	for (let it = 0; it < 15; it++) {
		const acc = centres.map(() => [0, 0, 0, 0]);
		for (const [r, g, b] of samples) { const a = acc[nearest(r, g, b)]; a[0] += r; a[1] += g; a[2] += b; a[3]++; }
		centres = centres.map((c, i) => (acc[i][3] ? [acc[i][0] / acc[i][3], acc[i][1] / acc[i][3], acc[i][2] / acc[i][3]] : c));
	}
	centres = centres.map((c) => c.map(Math.round));
	for (let p = 0; p < n; p++) {
		const i = p * 4;
		if (data[i + 3] < 128) { data[i + 3] = 0; continue; }
		const c = centres[nearest(data[i], data[i + 1], data[i + 2])];
		data[i] = c[0]; data[i + 1] = c[1]; data[i + 2] = c[2]; data[i + 3] = 255;
	}
	await sharp(data, { raw: { width: info.width, height: info.height, channels: 4 } }).png().toFile(output);
	console.log(`${input.split("/").pop()}: ${k} colours ${centres.map((c) => "#" + c.map((v) => v.toString(16).padStart(2, "0")).join("")).join(" ")}`);
})();