/* * Color Thief v2.0 * by Lokesh Dhakar - http://www.lokeshdhakar.com * * Thanks * ------ * Nick Rabinowitz - For creating quantize.js. * John Schulz - For clean up and optimization. @JFSIII * Nathan Spady - For adding drag and drop support to the demo page. * * License * ------- * Copyright 2011, 2015 Lokesh Dhakar * Released under the MIT license * https://raw.githubusercontent.com/lokesh/color-thief/master/LICENSE * * @license */ /* CanvasImage Class Class that wraps the html image element and canvas. It also simplifies some of the canvas context manipulation with a set of helper functions. */ var CanvasImage = function (image) { this.canvas = document.createElement('canvas'); this.context = this.canvas.getContext('2d'); document.body.appendChild(this.canvas); this.width = this.canvas.width = image.width; this.height = this.canvas.height = image.height; this.context.drawImage(image, 0, 0, this.width, this.height); }; CanvasImage.prototype.clear = function () { this.context.clearRect(0, 0, this.width, this.height); }; CanvasImage.prototype.update = function (imageData) { this.context.putImageData(imageData, 0, 0); }; CanvasImage.prototype.getPixelCount = function () { return this.width * this.height; }; CanvasImage.prototype.getImageData = function () { return this.context.getImageData(0, 0, this.width, this.height); }; CanvasImage.prototype.removeCanvas = function () { this.canvas.parentNode.removeChild(this.canvas); }; var ColorThief = function () {}; /* * getColor(sourceImage[, quality]) * returns {r: num, g: num, b: num} * * Use the median cut algorithm provided by quantize.js to cluster similar * colors and return the base color from the largest cluster. * * Quality is an optional argument. It needs to be an integer. 1 is the highest quality settings. * 10 is the default. There is a trade-off between quality and speed. The bigger the number, the * faster a color will be returned but the greater the likelihood that it will not be the visually * most dominant color. * * */ ColorThief.prototype.getColor = function(sourceImage, quality) { var palette = this.getPalette(sourceImage, 5, quality); var dominantColor = palette[0]; return dominantColor; }; /* * getPalette(sourceImage[, colorCount, quality]) * returns array[ {r: num, g: num, b: num}, {r: num, g: num, b: num}, ...] * * Use the median cut algorithm provided by quantize.js to cluster similar colors. * * colorCount determines the size of the palette; the number of colors returned. If not set, it * defaults to 10. * * BUGGY: Function does not always return the requested amount of colors. It can be +/- 2. * * quality is an optional argument. It needs to be an integer. 1 is the highest quality settings. * 10 is the default. There is a trade-off between quality and speed. The bigger the number, the * faster the palette generation but the greater the likelihood that colors will be missed. * * */ ColorThief.prototype.getPalette = function(sourceImage, colorCount, quality) { if (typeof colorCount === 'undefined' || colorCount < 2 || colorCount > 256) { colorCount = 10; } if (typeof quality === 'undefined' || quality < 1) { quality = 10; } // Create custom CanvasImage object var image = new CanvasImage(sourceImage); var imageData = image.getImageData(); var pixels = imageData.data; var pixelCount = image.getPixelCount(); // Store the RGB values in an array format suitable for quantize function var pixelArray = []; for (var i = 0, offset, r, g, b, a; i < pixelCount; i = i + quality) { offset = i * 4; r = pixels[offset + 0]; g = pixels[offset + 1]; b = pixels[offset + 2]; a = pixels[offset + 3]; // If pixel is mostly opaque and not white if (a >= 125) { if (!(r > 250 && g > 250 && b > 250)) { pixelArray.push([r, g, b]); } } } // Send array to quantize function which clusters values // using median cut algorithm var cmap = MMCQ.quantize(pixelArray, colorCount); var palette = cmap? cmap.palette() : null; // Clean up image.removeCanvas(); return palette; }; ColorThief.prototype.getColorFromUrl = function(imageUrl, callback, quality) { sourceImage = document.createElement("img"); var thief = this; sourceImage.addEventListener('load' , function(){ var palette = thief.getPalette(sourceImage, 5, quality); var dominantColor = palette[0]; callback(dominantColor, imageUrl); }); sourceImage.src = imageUrl }; ColorThief.prototype.getImageData = function(imageUrl, callback) { xhr = new XMLHttpRequest(); xhr.open('GET', imageUrl, true); xhr.responseType = 'arraybuffer' xhr.onload = function(e) { if (this.status == 200) { uInt8Array = new Uint8Array(this.response) i = uInt8Array.length binaryString = new Array(i); for (var i = 0; i < uInt8Array.length; i++){ binaryString[i] = String.fromCharCode(uInt8Array[i]) } data = binaryString.join('') base64 = window.btoa(data) callback ("data:image/png;base64,"+base64) } } xhr.send(); }; ColorThief.prototype.getColorAsync = function(imageUrl, callback, quality) { var thief = this; this.getImageData(imageUrl, function(imageData){ sourceImage = document.createElement("img"); sourceImage.addEventListener('load' , function(){ var palette = thief.getPalette(sourceImage, 5, quality); var dominantColor = palette[0]; callback(dominantColor, this); }); sourceImage.src = imageData; }); }; /*! * quantize.js Copyright 2008 Nick Rabinowitz. * Licensed under the MIT license: http://www.opensource.org/licenses/mit-license.php * @license */ // fill out a couple protovis dependencies /*! * Block below copied from Protovis: http://mbostock.github.com/protovis/ * Copyright 2010 Stanford Visualization Group * Licensed under the BSD License: http://www.opensource.org/licenses/bsd-license.php * @license */ if (!pv) { var pv = { map: function(array, f) { var o = {}; return f ? array.map(function(d, i) { o.index = i; return f.call(o, d); }) : array.slice(); }, naturalOrder: function(a, b) { return (a < b) ? -1 : ((a > b) ? 1 : 0); }, sum: function(array, f) { var o = {}; return array.reduce(f ? function(p, d, i) { o.index = i; return p + f.call(o, d); } : function(p, d) { return p + d; }, 0); }, max: function(array, f) { return Math.max.apply(null, f ? pv.map(array, f) : array); } }; } /** * Basic Javascript port of the MMCQ (modified median cut quantization) * algorithm from the Leptonica library (http://www.leptonica.com/). * Returns a color map you can use to map original pixels to the reduced * palette. Still a work in progress. * * @author Nick Rabinowitz * @example // array of pixels as [R,G,B] arrays var myPixels = [[190,197,190], [202,204,200], [207,214,210], [211,214,211], [205,207,207] // etc ]; var maxColors = 4; var cmap = MMCQ.quantize(myPixels, maxColors); var newPalette = cmap.palette(); var newPixels = myPixels.map(function(p) { return cmap.map(p); }); */ var MMCQ = (function() { // private constants var sigbits = 5, rshift = 8 - sigbits, maxIterations = 1000, fractByPopulations = 0.75; // get reduced-space color index for a pixel function getColorIndex(r, g, b) { return (r << (2 * sigbits)) + (g << sigbits) + b; } // Simple priority queue function PQueue(comparator) { var contents = [], sorted = false; function sort() { contents.sort(comparator); sorted = true; } return { push: function(o) { contents.push(o); sorted = false; }, peek: function(index) { if (!sorted) sort(); if (index===undefined) index = contents.length - 1; return contents[index]; }, pop: function() { if (!sorted) sort(); return contents.pop(); }, size: function() { return contents.length; }, map: function(f) { return contents.map(f); }, debug: function() { if (!sorted) sort(); return contents; } }; } // 3d color space box function VBox(r1, r2, g1, g2, b1, b2, histo) { var vbox = this; vbox.r1 = r1; vbox.r2 = r2; vbox.g1 = g1; vbox.g2 = g2; vbox.b1 = b1; vbox.b2 = b2; vbox.histo = histo; } VBox.prototype = { volume: function(force) { var vbox = this; if (!vbox._volume || force) { vbox._volume = ((vbox.r2 - vbox.r1 + 1) * (vbox.g2 - vbox.g1 + 1) * (vbox.b2 - vbox.b1 + 1)); } return vbox._volume; }, count: function(force) { var vbox = this, histo = vbox.histo; if (!vbox._count_set || force) { var npix = 0, index, i, j, k; for (i = vbox.r1; i <= vbox.r2; i++) { for (j = vbox.g1; j <= vbox.g2; j++) { for (k = vbox.b1; k <= vbox.b2; k++) { index = getColorIndex(i,j,k); npix += (histo[index] || 0); } } } vbox._count = npix; vbox._count_set = true; } return vbox._count; }, copy: function() { var vbox = this; return new VBox(vbox.r1, vbox.r2, vbox.g1, vbox.g2, vbox.b1, vbox.b2, vbox.histo); }, avg: function(force) { var vbox = this, histo = vbox.histo; if (!vbox._avg || force) { var ntot = 0, mult = 1 << (8 - sigbits), rsum = 0, gsum = 0, bsum = 0, hval, i, j, k, histoindex; for (i = vbox.r1; i <= vbox.r2; i++) { for (j = vbox.g1; j <= vbox.g2; j++) { for (k = vbox.b1; k <= vbox.b2; k++) { histoindex = getColorIndex(i,j,k); hval = histo[histoindex] || 0; ntot += hval; rsum += (hval * (i + 0.5) * mult); gsum += (hval * (j + 0.5) * mult); bsum += (hval * (k + 0.5) * mult); } } } if (ntot) { vbox._avg = [~~(rsum/ntot), ~~(gsum/ntot), ~~(bsum/ntot)]; } else { // console.log('empty box'); vbox._avg = [ ~~(mult * (vbox.r1 + vbox.r2 + 1) / 2), ~~(mult * (vbox.g1 + vbox.g2 + 1) / 2), ~~(mult * (vbox.b1 + vbox.b2 + 1) / 2) ]; } } return vbox._avg; }, contains: function(pixel) { var vbox = this, rval = pixel[0] >> rshift; gval = pixel[1] >> rshift; bval = pixel[2] >> rshift; return (rval >= vbox.r1 && rval <= vbox.r2 && gval >= vbox.g1 && gval <= vbox.g2 && bval >= vbox.b1 && bval <= vbox.b2); } }; // Color map function CMap() { this.vboxes = new PQueue(function(a,b) { return pv.naturalOrder( a.vbox.count()*a.vbox.volume(), b.vbox.count()*b.vbox.volume() ); }); } CMap.prototype = { push: function(vbox) { this.vboxes.push({ vbox: vbox, color: vbox.avg() }); }, palette: function() { return this.vboxes.map(function(vb) { return vb.color; }); }, size: function() { return this.vboxes.size(); }, map: function(color) { var vboxes = this.vboxes; for (var i=0; i 251 var idx = vboxes.length-1, highest = vboxes[idx].color; if (highest[0] > 251 && highest[1] > 251 && highest[2] > 251) vboxes[idx].color = [255,255,255]; } }; // histo (1-d array, giving the number of pixels in // each quantized region of color space), or null on error function getHisto(pixels) { var histosize = 1 << (3 * sigbits), histo = new Array(histosize), index, rval, gval, bval; pixels.forEach(function(pixel) { rval = pixel[0] >> rshift; gval = pixel[1] >> rshift; bval = pixel[2] >> rshift; index = getColorIndex(rval, gval, bval); histo[index] = (histo[index] || 0) + 1; }); return histo; } function vboxFromPixels(pixels, histo) { var rmin=1000000, rmax=0, gmin=1000000, gmax=0, bmin=1000000, bmax=0, rval, gval, bval; // find min/max pixels.forEach(function(pixel) { rval = pixel[0] >> rshift; gval = pixel[1] >> rshift; bval = pixel[2] >> rshift; if (rval < rmin) rmin = rval; else if (rval > rmax) rmax = rval; if (gval < gmin) gmin = gval; else if (gval > gmax) gmax = gval; if (bval < bmin) bmin = bval; else if (bval > bmax) bmax = bval; }); return new VBox(rmin, rmax, gmin, gmax, bmin, bmax, histo); } function medianCutApply(histo, vbox) { if (!vbox.count()) return; var rw = vbox.r2 - vbox.r1 + 1, gw = vbox.g2 - vbox.g1 + 1, bw = vbox.b2 - vbox.b1 + 1, maxw = pv.max([rw, gw, bw]); // only one pixel, no split if (vbox.count() == 1) { return [vbox.copy()]; } /* Find the partial sum arrays along the selected axis. */ var total = 0, partialsum = [], lookaheadsum = [], i, j, k, sum, index; if (maxw == rw) { for (i = vbox.r1; i <= vbox.r2; i++) { sum = 0; for (j = vbox.g1; j <= vbox.g2; j++) { for (k = vbox.b1; k <= vbox.b2; k++) { index = getColorIndex(i,j,k); sum += (histo[index] || 0); } } total += sum; partialsum[i] = total; } } else if (maxw == gw) { for (i = vbox.g1; i <= vbox.g2; i++) { sum = 0; for (j = vbox.r1; j <= vbox.r2; j++) { for (k = vbox.b1; k <= vbox.b2; k++) { index = getColorIndex(j,i,k); sum += (histo[index] || 0); } } total += sum; partialsum[i] = total; } } else { /* maxw == bw */ for (i = vbox.b1; i <= vbox.b2; i++) { sum = 0; for (j = vbox.r1; j <= vbox.r2; j++) { for (k = vbox.g1; k <= vbox.g2; k++) { index = getColorIndex(j,k,i); sum += (histo[index] || 0); } } total += sum; partialsum[i] = total; } } partialsum.forEach(function(d,i) { lookaheadsum[i] = total-d; }); function doCut(color) { var dim1 = color + '1', dim2 = color + '2', left, right, vbox1, vbox2, d2, count2=0; for (i = vbox[dim1]; i <= vbox[dim2]; i++) { if (partialsum[i] > total / 2) { vbox1 = vbox.copy(); vbox2 = vbox.copy(); left = i - vbox[dim1]; right = vbox[dim2] - i; if (left <= right) d2 = Math.min(vbox[dim2] - 1, ~~(i + right / 2)); else d2 = Math.max(vbox[dim1], ~~(i - 1 - left / 2)); // avoid 0-count boxes while (!partialsum[d2]) d2++; count2 = lookaheadsum[d2]; while (!count2 && partialsum[d2-1]) count2 = lookaheadsum[--d2]; // set dimensions vbox1[dim2] = d2; vbox2[dim1] = vbox1[dim2] + 1; // console.log('vbox counts:', vbox.count(), vbox1.count(), vbox2.count()); return [vbox1, vbox2]; } } } // determine the cut planes return maxw == rw ? doCut('r') : maxw == gw ? doCut('g') : doCut('b'); } function quantize(pixels, maxcolors) { // short-circuit if (!pixels.length || maxcolors < 2 || maxcolors > 256) { // console.log('wrong number of maxcolors'); return false; } // XXX: check color content and convert to grayscale if insufficient var histo = getHisto(pixels), histosize = 1 << (3 * sigbits); // check that we aren't below maxcolors already var nColors = 0; histo.forEach(function() { nColors++; }); if (nColors <= maxcolors) { // XXX: generate the new colors from the histo and return } // get the beginning vbox from the colors var vbox = vboxFromPixels(pixels, histo), pq = new PQueue(function(a,b) { return pv.naturalOrder(a.count(), b.count()); }); pq.push(vbox); // inner function to do the iteration function iter(lh, target) { var ncolors = 1, niters = 0, vbox; while (niters < maxIterations) { vbox = lh.pop(); if (!vbox.count()) { /* just put it back */ lh.push(vbox); niters++; continue; } // do the cut var vboxes = medianCutApply(histo, vbox), vbox1 = vboxes[0], vbox2 = vboxes[1]; if (!vbox1) { // console.log("vbox1 not defined; shouldn't happen!"); return; } lh.push(vbox1); if (vbox2) { /* vbox2 can be null */ lh.push(vbox2); ncolors++; } if (ncolors >= target) return; if (niters++ > maxIterations) { // console.log("infinite loop; perhaps too few pixels!"); return; } } } // first set of colors, sorted by population iter(pq, fractByPopulations * maxcolors); // Re-sort by the product of pixel occupancy times the size in color space. var pq2 = new PQueue(function(a,b) { return pv.naturalOrder(a.count()*a.volume(), b.count()*b.volume()); }); while (pq.size()) { pq2.push(pq.pop()); } // next set - generate the median cuts using the (npix * vol) sorting. iter(pq2, maxcolors - pq2.size()); // calculate the actual colors var cmap = new CMap(); while (pq2.size()) { cmap.push(pq2.pop()); } return cmap; } return { quantize: quantize }; })();