Refine gradients and remove isolated colors
This commit is contained in:
wuyanwanwu
+138
-7
@@ -201,7 +201,9 @@ function mergePerceptualColors(data: Uint8ClampedArray) {
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}).sort((a, b) => b.count - a.count);
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const clusters: ColorCluster[] = [];
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const mergeThreshold = 0.025;
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// Keep enough source-color resolution for broad gradients. The later MARD
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// selection still merges close colors globally and rejects tiny edge noise.
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const mergeThreshold = 0.015;
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for (const bin of bins) {
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let nearestIndex = -1;
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let nearestDistance = Number.POSITIVE_INFINITY;
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@@ -254,20 +256,145 @@ function chooseDistinctMardColors(clusters: ColorCluster[], maximum: number) {
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}
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const separated: BeadColor[] = [];
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const totalPixels = clusters.reduce((total, cluster) => total + cluster.count, 0);
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const minimumMardDistance = 0.035;
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const broadGradientDistance = 0.02;
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const broadColorThreshold = Math.max(12, totalPixels * 0.008);
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const ranked = [...candidates.values()].sort((a, b) => b.score - a.score || a.error / a.count - b.error / b.count);
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for (const candidate of ranked) {
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const requiredDistance = candidate.count >= broadColorThreshold ? broadGradientDistance : minimumMardDistance;
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if (separated.every((selected) => oklabDistance(candidate.color.lab, selected.lab) >= requiredDistance)) {
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if (separated.every((selected) => oklabDistance(candidate.color.lab, selected.lab) >= minimumMardDistance)) {
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separated.push(candidate.color);
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}
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}
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return separated.slice(0, Math.max(0, Math.min(maximum, separated.length)));
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}
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function matchClustersToPalette(clusters: ColorCluster[], limitedPalette: BeadColor[], colorLimit: number) {
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const matches = clusters.map((cluster) => nearestColor(cluster.lab, limitedPalette));
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if (colorLimit < 12) return matches;
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// A large, smooth gradient may contain several useful MARD steps which the
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// global minimum-distance filter deliberately merges. Let only substantial
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// source clusters recover their accurate shade; tiny edge colors stay out.
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const totalPixels = clusters.reduce((total, cluster) => total + cluster.count, 0);
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const broadClusterThreshold = Math.max(24, totalPixels * 0.012);
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const maximumExtraShades = Math.min(8, Math.max(0, colorLimit - limitedPalette.length));
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const extraShades: BeadColor[] = [];
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const rankedClusters = clusters
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.map((cluster, index) => ({ cluster, index, exact: nearestColor(cluster.lab, PALETTE) }))
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.filter(({ cluster, exact, index }) => cluster.count >= broadClusterThreshold && exact.code !== matches[index].code)
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.sort((a, b) => b.cluster.count - a.cluster.count);
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for (const candidate of rankedClusters) {
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if (extraShades.length >= maximumExtraShades) break;
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if (extraShades.some((color) => color.code === candidate.exact.code)) {
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matches[candidate.index] = candidate.exact;
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continue;
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}
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const nearestSelectedDistance = Math.min(...limitedPalette.map((color) => oklabDistance(color.lab, candidate.exact.lab)));
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if (nearestSelectedDistance < 0.018) continue;
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extraShades.push(candidate.exact);
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matches[candidate.index] = candidate.exact;
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}
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return matches;
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}
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function preserveSmoothGradientSteps(
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colors: Array<BeadColor | null>,
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sourceData: Uint8ClampedArray,
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width: number,
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height: number,
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colorLimit: number,
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) {
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if (colorLimit < 12) return colors;
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const result = [...colors];
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const sourceLabs: Array<Oklab | null> = [];
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for (let index = 0; index < sourceData.length; index += 4) {
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sourceLabs.push(sourceData[index + 3] < TRANSPARENT_ALPHA_THRESHOLD
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? null
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: rgbToOklab([sourceData[index], sourceData[index + 1], sourceData[index + 2]]));
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}
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const smoothMask = new Uint8Array(width * height);
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const directions = [[-1, 0], [1, 0], [0, -1], [0, 1]];
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for (let row = 1; row < height - 1; row++) {
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for (let column = 1; column < width - 1; column++) {
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const index = row * width + column;
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const current = sourceLabs[index];
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if (!current) continue;
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let maximumNeighborDistance = 0;
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for (const [rowOffset, columnOffset] of directions) {
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const neighbor = sourceLabs[(row + rowOffset) * width + column + columnOffset];
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if (!neighbor) { maximumNeighborDistance = Number.POSITIVE_INFINITY; break; }
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maximumNeighborDistance = Math.max(maximumNeighborDistance, oklabDistance(current, neighbor));
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}
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if (maximumNeighborDistance <= 0.018) smoothMask[index] = 1;
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}
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}
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// Require a real two-dimensional smooth patch, so a one-cell antialiased
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// outline can never qualify as a gradient.
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const gradientPalette = new Set<string>();
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for (let row = 2; row < height - 2; row++) {
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for (let column = 2; column < width - 2; column++) {
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const index = row * width + column;
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if (!smoothMask[index]) continue;
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let smoothNeighbors = 0;
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for (let rowOffset = -1; rowOffset <= 1; rowOffset++) {
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for (let columnOffset = -1; columnOffset <= 1; columnOffset++) {
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if (smoothMask[(row + rowOffset) * width + column + columnOffset]) smoothNeighbors += 1;
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}
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}
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if (smoothNeighbors < 7) continue;
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const sourceLab = sourceLabs[index]!;
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const sourceChroma = Math.hypot(sourceLab[1], sourceLab[2]);
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// Near-neutral pixels should use the neutral MARD series. Otherwise a
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// barely visible numerical hue can create a conspicuous lavender/pink
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// stripe inside an otherwise blue-to-cream gradient.
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const gradientCandidates = sourceChroma < 0.035
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? PALETTE.filter((color) => color.code.startsWith("H"))
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: PALETTE;
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const exact = nearestColor(sourceLab, gradientCandidates);
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if (!gradientPalette.has(exact.code) && gradientPalette.size >= 8) continue;
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gradientPalette.add(exact.code);
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result[index] = exact;
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}
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}
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return result;
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}
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function cleanGloballyRareIsolatedColors(colors: Array<BeadColor | null>, width: number, height: number) {
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const usage = new Map<string, number>();
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colors.forEach((color) => { if (color) usage.set(color.code, (usage.get(color.code) ?? 0) + 1); });
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const cleaned = [...colors];
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let changed = 0;
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for (let row = 0; row < height; row++) {
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for (let column = 0; column < width; column++) {
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const index = row * width + column;
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const current = colors[index];
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if (!current || (usage.get(current.code) ?? 0) > 2) continue;
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const neighbors = new Map<string, { color: BeadColor; count: number }>();
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for (let rowOffset = -1; rowOffset <= 1; rowOffset++) {
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for (let columnOffset = -1; columnOffset <= 1; columnOffset++) {
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if (rowOffset === 0 && columnOffset === 0) continue;
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const neighborRow = row + rowOffset;
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const neighborColumn = column + columnOffset;
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if (neighborRow < 0 || neighborColumn < 0 || neighborRow >= height || neighborColumn >= width) continue;
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const neighbor = colors[neighborRow * width + neighborColumn];
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if (!neighbor || neighbor.code === current.code) continue;
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const entry = neighbors.get(neighbor.code) ?? { color: neighbor, count: 0 };
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entry.count += 1;
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neighbors.set(neighbor.code, entry);
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}
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}
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const majority = [...neighbors.values()].sort((a, b) => b.count - a.count)[0];
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if (!majority) continue;
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const requiredSupport = (usage.get(current.code) ?? 0) === 1 ? 3 : 5;
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if (majority.count < requiredSupport) continue;
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cleaned[index] = majority.color;
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changed += 1;
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}
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}
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return { colors: cleaned, changed };
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}
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function sampleDominantRegions(
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image: HTMLImageElement,
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width: number,
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@@ -630,7 +757,7 @@ export default function Home() {
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}
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const { pixelKeys, clusters, binClusters } = mergePerceptualColors(data);
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const limitedPalette = chooseDistinctMardColors(clusters, Math.max(2, Math.min(colorLimit, PALETTE.length)));
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const clusterMatches = clusters.map((cluster) => nearestColor(cluster.lab, limitedPalette));
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const clusterMatches = matchClustersToPalette(clusters, limitedPalette, colorLimit);
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let matchedColors: Array<BeadColor | null> = pixelKeys.map((key) => key === null ? null : clusterMatches[binClusters.get(key) ?? 0]);
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let cleanedCount = 0;
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if (dominantConfidence) {
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@@ -640,6 +767,10 @@ export default function Home() {
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const transitionCleaned = cleanThinTransitionBands(matchedColors, width, height);
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matchedColors = transitionCleaned.colors;
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cleanedCount += transitionCleaned.changed;
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matchedColors = preserveSmoothGradientSteps(matchedColors, data, width, height, colorLimit);
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const rareCleaned = cleanGloballyRareIsolatedColors(matchedColors, width, height);
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matchedColors = rareCleaned.colors;
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cleanedCount += rareCleaned.changed;
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}
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const converted = matchedColors.map((color) => ({ color }));
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setGridWidth(width);
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@@ -11,7 +11,7 @@
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"name": "rolldown-runtime"
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},
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"app/page.tsx": {
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"file": "_next/static/chunks/page-Clx65Ifw.js",
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"file": "_next/static/chunks/page-5ZnMML26.js",
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"name": "page",
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"src": "app/page.tsx",
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"isDynamicEntry": true,
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@@ -21,7 +21,7 @@
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]
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},
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"node_modules/vinext/dist/shims/layout-segment-context.js": {
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"file": "_next/static/chunks/layout-segment-context-BVJGUT0n.js",
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"file": "_next/static/chunks/layout-segment-context-Bq1X1g2W.js",
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"name": "layout-segment-context",
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"src": "node_modules/vinext/dist/shims/layout-segment-context.js",
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"isDynamicEntry": true,
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@@ -32,7 +32,7 @@
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]
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},
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"virtual:vinext-app-browser-entry": {
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"file": "_next/static/chunks/index-iZ0Yke16.js",
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"file": "_next/static/chunks/index-ByP43Bdw.js",
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"name": "index",
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"src": "virtual:vinext-app-browser-entry",
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"isEntry": true,
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+2
-2
@@ -1,2 +1,2 @@
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<!DOCTYPE html><html lang="zh-CN"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="/_next/static/css/index.DWpRPKap.css" data-rsc-css-href="/_next/static/css/index.DWpRPKap.css" data-precedence="vite-rsc/importer-resources"/><link rel="modulepreload" fetchPriority="low" href="/_next/static/chunks/index-iZ0Yke16.js"/><script src="/_next/static/chunks/rolldown-runtime-C60lm6uB.js" type="module" async=""></script><script src="/_next/static/chunks/framework-BgSIrAUN.js" type="module" async=""></script><meta name="robots" content="noindex"/><title>豆格工坊｜图片转拼豆图纸</title><meta name="description" content="在浏览器中把图片转换为拼豆像素图纸，按色号、名称或像素格筛选颜色。"/><title>404: This page could not be found.</title><script>Object.assign(((self[Symbol.for("vinext.navigationRuntime")]??={bootstrap:{routeManifest:null},functions:{}}).bootstrap.rsc??={rsc:[]}),{params:{},nav:{"pathname":"/__vinext_nonexistent_for_404__","searchParams":[]}})</script><link rel="modulepreload" href="/_next/static/chunks/index-iZ0Yke16.js" />
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</head><body><div style="font-family:system-ui,"Segoe UI",Roboto,Helvetica,Arial,sans-serif,"Apple Color Emoji","Segoe UI Emoji";height:100vh;text-align:center;display:flex;flex-direction:column;align-items:center;justify-content:center"><div><style>body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}</style><h1 class="next-error-h1" style="display:inline-block;margin:0 20px 0 0;padding:0 23px 0 0;font-size:24px;font-weight:500;vertical-align:top;line-height:49px">404</h1><div style="display:inline-block"><h2 style="font-size:14px;font-weight:400;line-height:49px;margin:0">This page could not be found.</h2></div></div></div><script type="module" src="/_next/static/chunks/index-iZ0Yke16.js" id="_R_" async=""></script><script>((self[Symbol.for("vinext.navigationRuntime")]??={bootstrap:{routeManifest:null},functions:{}}).bootstrap.rsc??={rsc:[]}).rsc.push("1:\"$Sreact.fragment\"\n")</script><script>((self[Symbol.for("vinext.navigationRuntime")]??={bootstrap:{routeManifest:null},functions:{}}).bootstrap.rsc??={rsc:[]}).rsc.push(":HL[\"/_next/static/css/index.DWpRPKap.css\",\"style\" ]\n")</script><script>((self[Symbol.for("vinext.navigationRuntime")]??={bootstrap:{routeManifest:null},functions:{}}).bootstrap.rsc??={rsc:[]}).rsc.push("0:{\"__route\":\"route:/__vinext_nonexistent_for_404__\",\"__interceptionContext\":null,\"__layoutIds\":[],\"__rootLayout\":null,\"route:/__vinext_nonexistent_for_404__\":[[[\"$\",\"link\",\"css:/_next/static/css/index.DWpRPKap.css\",{\"rel\":\"stylesheet\",\"precedence\":\"vite-rsc/importer-resources\",\"href\":\"/_next/static/css/index.DWpRPKap.css\",\"data-rsc-css-href\":\"/_next/static/css/index.DWpRPKap.css\"}],\"$undefined\"],[\"$\",\"html\",null,{\"lang\":\"zh-CN\",\"children\":[\"$\",\"body\",null,{\"children\":[[\"$\",\"meta\",\"charset\",{\"charSet\":\"utf-8\"}],[\"$\",\"meta\",\"robots\",{\"name\":\"robots\",\"content\":\"noindex\"}],[\"$\",\"$1\",\"metadata\",{\"children\":[[\"$\",\"title\",\"0\",{\"children\":\"豆格工坊｜图片转拼豆图纸\"}],[\"$\",\"meta\",\"1\",{\"name\":\"description\",\"content\":\"在浏览器中把图片转换为拼豆像素图纸，按色号、名称或像素格筛选颜色。\"}]]}],[\"$\",\"$1\",\"viewport\",{\"children\":[[\"$\",\"meta\",\"0\",{\"name\":\"viewport\",\"content\":\"width=device-width, initial-scale=1\"}]]}],[[\"$\",\"title\",null,{\"children\":\"404: This page could not be found.\"}],[\"$\",\"div\",null,{\"style\":{\"fontFamily\":\"system-ui,\\\"Segoe UI\\\",Roboto,Helvetica,Arial,sans-serif,\\\"Apple Color Emoji\\\",\\\"Segoe UI Emoji\\\"\",\"height\":\"100vh\",\"textAlign\":\"center\",\"display\":\"flex\",\"flexDirection\":\"column\",\"alignItems\":\"center\",\"justifyContent\":\"center\"},\"children\":[\"$\",\"div\",null,{\"children\":[[\"$\",\"style\",null,{\"dangerouslySetInnerHTML\":{\"__html\":\"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}\"}}],[\"$\",\"h1\",null,{\"className\":\"next-error-h1\",\"style\":{\"display\":\"inline-block\",\"margin\":\"0 20px 0 0\",\"padding\":\"0 23px 0 0\",\"fontSize\":24,\"fontWeight\":500,\"verticalAlign\":\"top\",\"lineHeight\":\"49px\"},\"children\":404}],[\"$\",\"div\",null,{\"style\":{\"display\":\"inline-block\"},\"children\":[\"$\",\"h2\",null,{\"style\":{\"fontSize\":14,\"fontWeight\":400,\"lineHeight\":\"49px\",\"margin\":0},\"children\":\"This page could not be found.\"}]}]]}]}]]]}]}]]}\n")</script><script>((self[Symbol.for("vinext.navigationRuntime")]??={bootstrap:{routeManifest:null},functions:{}}).bootstrap.rsc??={rsc:[]}).done=true</script></body></html>
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<!DOCTYPE html><html lang="zh-CN"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="stylesheet" href="/_next/static/css/index.Dq42BzaZ.css" data-rsc-css-href="/_next/static/css/index.Dq42BzaZ.css" data-precedence="vite-rsc/importer-resources"/><link rel="modulepreload" fetchPriority="low" href="/_next/static/chunks/index-ByP43Bdw.js"/><script src="/_next/static/chunks/rolldown-runtime-C60lm6uB.js" type="module" async=""></script><script src="/_next/static/chunks/framework-BgSIrAUN.js" type="module" async=""></script><meta name="robots" content="noindex"/><title>豆格工坊｜图片转拼豆图纸</title><meta name="description" content="在浏览器中把图片转换为拼豆像素图纸，按色号、名称或像素格筛选颜色。"/><title>404: This page could not be found.</title><script>Object.assign(((self[Symbol.for("vinext.navigationRuntime")]??={bootstrap:{routeManifest:null},functions:{}}).bootstrap.rsc??={rsc:[]}),{params:{},nav:{"pathname":"/__vinext_nonexistent_for_404__","searchParams":[]}})</script><link rel="modulepreload" href="/_next/static/chunks/index-ByP43Bdw.js" />
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Reference in New Issue
Block a user