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start migrating to TS, update eslint config
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180
src/color-thief.ts
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180
src/color-thief.ts
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import quantize from '../node_modules/@lokesh.dhakar/quantize/dist/index.mjs';
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import core from './core.js';
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/*
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* Color Thief v2.4.0
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* by Lokesh Dhakar - http://www.lokeshdhakar.com
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*
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* Thanks
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* ------
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* Nick Rabinowitz - For creating quantize.js.
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* John Schulz - For clean up and optimization. @JFSIII
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* Nathan Spady - For adding drag and drop support to the demo page.
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*
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* License
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* -------
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* Copyright Lokesh Dhakar
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* Released under the MIT license
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* https://raw.githubusercontent.com/lokesh/color-thief/master/LICENSE
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*
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* @license
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*/
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/*
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CanvasImage Class
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Class that wraps the html image element and canvas.
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It also simplifies some of the canvas context manipulation
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with a set of helper functions.
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*/
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const CanvasImage = function (image: HTMLImageElement) {
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this.canvas = document.createElement('canvas');
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this.context = this.canvas.getContext('2d');
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this.width = this.canvas.width = image.naturalWidth;
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this.height = this.canvas.height = image.naturalHeight;
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this.context.drawImage(image, 0, 0, this.width, this.height);
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};
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CanvasImage.prototype.getImageData = function () {
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return this.context.getImageData(0, 0, this.width, this.height);
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};
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interface ColorThiefResult {
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r: number;
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g: number;
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b: number;
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}
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class ColorThief {
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/**
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* Use the median cut algorithm provided by quantize.js to cluster similar
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* colors and return the base color from the largest cluster.
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* @param {HTMLImageElement} sourceImage:HTMLImageElement
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* @param {number} quality Quality is an optional argument. It needs to be an integer. 1 is the highest quality settings.
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* 10 is the default. There is a trade-off between quality and speed. The bigger the number, the
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* faster a color will be returned but the greater the likelihood that it will not be the visually
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* most dominant color.
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* @returns {ColorThiefResult} returns {r: num, g: num, b: num}
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*/
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getColor(
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sourceImage: HTMLImageElement,
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quality: number = 10,
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): ColorThiefResult {
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const palette = this.getPalette(sourceImage, 5, quality);
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return palette[0];
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}
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/**
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* Use the median cut algorithm provided by quantize.js to cluster similar colors.
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* @param {HTMLImageElement} sourceImage The image you want to have processed, as an HTMLImageElement
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* @param {number?} colorCount colorCount determines the size of the palette; the number of colors returned. If not set, it
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* defaults to 10.
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* @param {number?} quality quality is an optional argument. It needs to be an integer. 1 is the highest quality settings.
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* 10 is the default. There is a trade-off between quality and speed. The bigger the number, the
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* faster the palette generation but the greater the likelihood that colors will be missed.
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* @returns {ColorThiefResult[]} returns array[ {r: num, g: num, b: num}, {r: num, g: num, b: num}, ...]
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*/
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getPalette(
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sourceImage: HTMLImageElement,
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colorCount?: number,
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quality: number = 10,
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): ColorThiefResult[] {
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const options = core.validateOptions({
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colorCount,
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quality,
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});
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// Create custom CanvasImage object
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const image = new CanvasImage(sourceImage);
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const imageData = image.getImageData();
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const pixelCount = image.width * image.height;
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const pixelArray = core.createPixelArray(
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imageData.data,
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pixelCount,
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options.quality,
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);
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// Send array to quantize function which clusters values
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// using median cut algorithm
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const cmap = quantize(pixelArray, options.colorCount);
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const palette = cmap ? cmap.palette() : null;
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return palette;
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}
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/**
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* Description
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* @param {any} imageUrl
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* @param {any} callback
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* @param {any} quality
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* @returns {any}
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*/
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getColorFromUrl(imageUrl, callback, quality) {
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const sourceImage = document.createElement('img');
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sourceImage.addEventListener('load', () => {
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const palette = this.getPalette(sourceImage, 5, quality);
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const dominantColor = palette[0];
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callback(dominantColor, imageUrl);
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});
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sourceImage.src = imageUrl;
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}
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/**
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* Description
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* @param {string} imageUrl
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* @param {string} callback
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* @returns {void}
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*/
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getImageData(imageUrl: string, callback) {
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let xhr = new XMLHttpRequest();
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xhr.open('GET', imageUrl, true);
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xhr.responseType = 'arraybuffer';
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fetch(imageUrl).then((res) => {
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if (res.status === 200) {
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res.arrayBuffer().then((response) => {
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const uInt8Array = new Uint8Array(response);
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let binaryString = new Array(uInt8Array.length);
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for (let i = 0; i < uInt8Array.length; i++) {
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binaryString[i] = String.fromCharCode(uInt8Array[i]);
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}
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let data = binaryString.join('');
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let base64 = window.btoa(data);
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});
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}
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});
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xhr.onload = function () {
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if (this.status == 200) {
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let uInt8Array = new Uint8Array(this.response);
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callback('data:image/png;base64,' + base64);
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}
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};
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xhr.send();
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}
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/**
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* Description
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* @param {any} imageUrl
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* @param {any} callback
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* @param {any} quality
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* @returns {any}
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*/
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getColorAsync = function (imageUrl, callback, quality) {
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const thief = this;
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this.getImageData(imageUrl, function (imageData) {
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const sourceImage = document.createElement('img');
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sourceImage.addEventListener('load', function () {
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const palette = thief.getPalette(sourceImage, 5, quality);
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const dominantColor = palette[0];
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callback(dominantColor, this);
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});
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sourceImage.src = imageData;
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});
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};
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}
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export default ColorThief;
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