imagerot
Version:
A lightweight, cross-environment image library for applying unique effects via raw image buffers.
99 lines (98 loc) • 4.46 kB
JavaScript
;
var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
return new (P || (P = Promise))(function (resolve, reject) {
function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
step((generator = generator.apply(thisArg, _arguments || [])).next());
});
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.quadtree = void 0;
const quadtree = (_a, ...args_1) => __awaiter(void 0, [_a, ...args_1], void 0, function* ({ data, width, height }, options = {}) {
var _b, _c;
if (data.length === 0)
return data;
const maxDepth = (_b = options.maxDepth) !== null && _b !== void 0 ? _b : 8;
const varianceThreshold = (_c = options.varianceThreshold) !== null && _c !== void 0 ? _c : 50;
// Helper to compute average color and variance for a square region
const computeStats = (x, y, size) => {
let sumR = 0, sumG = 0, sumB = 0;
let sumSqR = 0, sumSqG = 0, sumSqB = 0;
const pixelCount = size * size;
for (let dy = 0; dy < size; dy++) {
for (let dx = 0; dx < size; dx++) {
const px = x + dx;
const py = y + dy;
if (px >= width || py >= height)
continue; // Clamp to bounds
const idx = (py * width + px) * 4;
const r = data[idx];
const g = data[idx + 1];
const b = data[idx + 2];
sumR += r;
sumG += g;
sumB += b;
sumSqR += r * r;
sumSqG += g * g;
sumSqB += b * b;
}
}
const avgR = sumR / pixelCount;
const avgG = sumG / pixelCount;
const avgB = sumB / pixelCount;
// Variance as average squared difference (for RGB combined)
const varR = (sumSqR / pixelCount) - avgR * avgR;
const varG = (sumSqG / pixelCount) - avgG * avgG;
const varB = (sumSqB / pixelCount) - avgB * avgB;
const variance = (varR + varG + varB) / 3;
return { avgR, avgG, avgB, variance };
};
// Recursive function to build the quadtree
const buildTree = (x, y, size, depth) => {
const { avgR, avgG, avgB, variance } = computeStats(x, y, size);
const node = { x, y, size, averageR: avgR, averageG: avgG, averageB: avgB };
if (variance > varianceThreshold && depth < maxDepth && size > 1) {
const half = Math.floor(size / 2);
node.children = [
buildTree(x, y, half, depth + 1), // Top-left
buildTree(x + half, y, half, depth + 1), // Top-right
buildTree(x, y + half, half, depth + 1), // Bottom-left
buildTree(x + half, y + half, half, depth + 1) // Bottom-right
];
}
return node;
};
// Build the root quadtree (full image)
const root = buildTree(0, 0, Math.min(width, height), 0); // Assume square for simplicity; adjust if needed
// Function to fill the buffer with average colors from leaf nodes
const fillBuffer = (node) => {
if (!node.children) {
// Leaf: fill the region with average color
const r = Math.floor(node.averageR);
const g = Math.floor(node.averageG);
const b = Math.floor(node.averageB);
for (let dy = 0; dy < node.size; dy++) {
for (let dx = 0; dx < node.size; dx++) {
const px = node.x + dx;
const py = node.y + dy;
if (px >= width || py >= height)
continue;
const idx = (py * width + px) * 4;
data[idx] = r;
data[idx + 1] = g;
data[idx + 2] = b;
// Alpha unchanged
}
}
}
else {
// Recurse on children
node.children.forEach(fillBuffer);
}
};
fillBuffer(root);
return data;
});
exports.quadtree = quadtree;