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{"version":3,"file":"color-thief.mjs","sources":["../node_modules/quantize/dist/index.mjs","../src/color-thief.js"],"sourcesContent":["/*\n * quantize.js Copyright 2008 Nick Rabinowitz\n * Ported to node.js by Olivier Lesnicki\n * Licensed under the MIT license: http://www.opensource.org/licenses/mit-license.php\n */\n// fill out a couple protovis dependencies\n\n/*\n * Block below copied from Protovis: http://mbostock.github.com/protovis/\n * Copyright 2010 Stanford Visualization Group\n * Licensed under the BSD License: http://www.opensource.org/licenses/bsd-license.php\n */\nif (!pv) {\n var pv = {\n map: function (array, f) {\n var o = {};\n return f ? array.map(function (d, i) {\n o.index = i;\n return f.call(o, d);\n }) : array.slice();\n },\n naturalOrder: function (a, b) {\n return a < b ? -1 : a > b ? 1 : 0;\n },\n sum: function (array, f) {\n var o = {};\n return array.reduce(f ? function (p, d, i) {\n o.index = i;\n return p + f.call(o, d);\n } : function (p, d) {\n return p + d;\n }, 0);\n },\n max: function (array, f) {\n return Math.max.apply(null, f ? pv.map(array, f) : array);\n }\n };\n}\n/**\n * Basic Javascript port of the MMCQ (modified median cut quantization)\n * algorithm from the Leptonica library (http://www.leptonica.com/).\n * Returns a color map you can use to map original pixels to the reduced\n * palette. Still a work in progress.\n * \n * @author Nick Rabinowitz\n * @example\n \n// array of pixels as [R,G,B] arrays\nvar myPixels = [[190,197,190], [202,204,200], [207,214,210], [211,214,211], [205,207,207]\n // etc\n ];\nvar maxColors = 4;\n \nvar cmap = MMCQ.quantize(myPixels, maxColors);\nvar newPalette = cmap.palette();\nvar newPixels = myPixels.map(function(p) { \n return cmap.map(p); \n});\n \n */\n\n\nvar MMCQ = function () {\n // private constants\n var sigbits = 5,\n rshift = 8 - sigbits,\n maxIterations = 1000,\n fractByPopulations = 0.75; // get reduced-space color index for a pixel\n\n function getColorIndex(r, g, b) {\n return (r << 2 * sigbits) + (g << sigbits) + b;\n } // Simple priority queue\n\n\n function PQueue(comparator) {\n var contents = [],\n sorted = false;\n\n function sort() {\n contents.sort(comparator);\n sorted = true;\n }\n\n return {\n push: function (o) {\n contents.push(o);\n sorted = false;\n },\n peek: function (index) {\n if (!sorted) { sort(); }\n if (index === undefined) { index = contents.length - 1; }\n return contents[index];\n },\n pop: function () {\n if (!sorted) { sort(); }\n return contents.pop();\n },\n size: function () {\n return contents.length;\n },\n map: function (f) {\n return contents.map(f);\n },\n debug: function () {\n if (!sorted) { sort(); }\n return contents;\n }\n };\n } // 3d color space box\n\n\n function VBox(r1, r2, g1, g2, b1, b2, histo) {\n var vbox = this;\n vbox.r1 = r1;\n vbox.r2 = r2;\n vbox.g1 = g1;\n vbox.g2 = g2;\n vbox.b1 = b1;\n vbox.b2 = b2;\n vbox.histo = histo;\n }\n\n VBox.prototype = {\n volume: function (force) {\n var vbox = this;\n\n if (!vbox._volume || force) {\n vbox._volume = (vbox.r2 - vbox.r1 + 1) * (vbox.g2 - vbox.g1 + 1) * (vbox.b2 - vbox.b1 + 1);\n }\n\n return vbox._volume;\n },\n count: function (force) {\n var vbox = this,\n histo = vbox.histo;\n\n if (!vbox._count_set || force) {\n var npix = 0,\n i,\n j,\n k,\n index;\n\n for (i = vbox.r1; i <= vbox.r2; i++) {\n for (j = vbox.g1; j <= vbox.g2; j++) {\n for (k = vbox.b1; k <= vbox.b2; k++) {\n index = getColorIndex(i, j, k);\n npix += histo[index] || 0;\n }\n }\n }\n\n vbox._count = npix;\n vbox._count_set = true;\n }\n\n return vbox._count;\n },\n copy: function () {\n var vbox = this;\n return new VBox(vbox.r1, vbox.r2, vbox.g1, vbox.g2, vbox.b1, vbox.b2, vbox.histo);\n },\n avg: function (force) {\n var vbox = this,\n histo = vbox.histo;\n\n if (!vbox._avg || force) {\n var ntot = 0,\n mult = 1 << 8 - sigbits,\n rsum = 0,\n gsum = 0,\n bsum = 0,\n hval,\n i,\n j,\n k,\n histoindex;\n\n for (i = vbox.r1; i <= vbox.r2; i++) {\n for (j = vbox.g1; j <= vbox.g2; j++) {\n for (k = vbox.b1; k <= vbox.b2; k++) {\n histoindex = getColorIndex(i, j, k);\n hval = histo[histoindex] || 0;\n ntot += hval;\n rsum += hval * (i + 0.5) * mult;\n gsum += hval * (j + 0.5) * mult;\n bsum += hval * (k + 0.5) * mult;\n }\n }\n }\n\n if (ntot) {\n vbox._avg = [~~(rsum / ntot), ~~(gsum / ntot), ~~(bsum / ntot)];\n } else {\n //console.log('empty box');\n vbox._avg = [~~(mult * (vbox.r1 + vbox.r2 + 1) / 2), ~~(mult * (vbox.g1 + vbox.g2 + 1) / 2), ~~(mult * (vbox.b1 + vbox.b2 + 1) / 2)];\n }\n }\n\n return vbox._avg;\n },\n contains: function (pixel) {\n var vbox = this,\n rval = pixel[0] >> rshift;\n gval = pixel[1] >> rshift;\n bval = pixel[2] >> rshift;\n return rval >= vbox.r1 && rval <= vbox.r2 && gval >= vbox.g1 && gval <= vbox.g2 && bval >= vbox.b1 && bval <= vbox.b2;\n }\n }; // Color map\n\n function CMap() {\n this.vboxes = new PQueue(function (a, b) {\n return pv.naturalOrder(a.vbox.count() * a.vbox.volume(), b.vbox.count() * b.vbox.volume());\n });\n }\n\n CMap.prototype = {\n push: function (vbox) {\n this.vboxes.push({\n vbox: vbox,\n color: vbox.avg()\n });\n },\n palette: function () {\n return this.vboxes.map(function (vb) {\n return vb.color;\n });\n },\n size: function () {\n return this.vboxes.size();\n },\n map: function (color) {\n var vboxes = this.vboxes;\n\n for (var i = 0; i < vboxes.size(); i++) {\n if (vboxes.peek(i).vbox.contains(color)) {\n return vboxes.peek(i).color;\n }\n }\n\n return this.nearest(color);\n },\n nearest: function (color) {\n var vboxes = this.vboxes,\n d1,\n d2,\n pColor;\n\n for (var i = 0; i < vboxes.size(); i++) {\n d2 = Math.sqrt(Math.pow(color[0] - vboxes.peek(i).color[0], 2) + Math.pow(color[1] - vboxes.peek(i).color[1], 2) + Math.pow(color[2] - vboxes.peek(i).color[2], 2));\n\n if (d2 < d1 || d1 === undefined) {\n d1 = d2;\n pColor = vboxes.peek(i).color;\n }\n }\n\n return pColor;\n },\n forcebw: function () {\n // XXX: won't work yet\n var vboxes = this.vboxes;\n vboxes.sort(function (a, b) {\n return pv.naturalOrder(pv.sum(a.color), pv.sum(b.color));\n }); // force darkest color to black if everything < 5\n\n var lowest = vboxes[0].color;\n if (lowest[0] < 5 && lowest[1] < 5 && lowest[2] < 5) { vboxes[0].color = [0, 0, 0]; } // force lightest color to white if everything > 251\n\n var idx = vboxes.length - 1,\n highest = vboxes[idx].color;\n if (highest[0] > 251 && highest[1] > 251 && highest[2] > 251) { vboxes[idx].color = [255, 255, 255]; }\n }\n }; // histo (1-d array, giving the number of pixels in\n // each quantized region of color space), or null on error\n\n function getHisto(pixels) {\n var histosize = 1 << 3 * sigbits,\n histo = new Array(histosize),\n index,\n rval,\n gval,\n bval;\n pixels.forEach(function (pixel) {\n rval = pixel[0] >> rshift;\n gval = pixel[1] >> rshift;\n bval = pixel[2] >> rshift;\n index = getColorIndex(rval, gval, bval);\n histo[index] = (histo[index] || 0) + 1;\n });\n return histo;\n }\n\n function vboxFromPixels(pixels, histo) {\n var rmin = 1000000,\n rmax = 0,\n gmin = 1000000,\n gmax = 0,\n bmin = 1000000,\n bmax = 0,\n rval,\n gval,\n bval; // find min/max\n\n pixels.forEach(function (pixel) {\n rval = pixel[0] >> rshift;\n gval = pixel[1] >> rshift;\n bval = pixel[2] >> rshift;\n if (rval < rmin) { rmin = rval; }else if (rval > rmax) { rmax = rval; }\n if (gval < gmin) { gmin = gval; }else if (gval > gmax) { gmax = gval; }\n if (bval < bmin) { bmin = bval; }else if (bval > bmax) { bmax = bval; }\n });\n return new VBox(rmin, rmax, gmin, gmax, bmin, bmax, histo);\n }\n\n function medianCutApply(histo, vbox) {\n if (!vbox.count()) { return; }\n var rw = vbox.r2 - vbox.r1 + 1,\n gw = vbox.g2 - vbox.g1 + 1,\n bw = vbox.b2 - vbox.b1 + 1,\n maxw = pv.max([rw, gw, bw]); // only one pixel, no split\n\n if (vbox.count() == 1) {\n return [vbox.copy()];\n }\n /* Find the partial sum arrays along the selected axis. */\n\n\n var total = 0,\n partialsum = [],\n lookaheadsum = [],\n i,\n j,\n k,\n sum,\n index;\n\n if (maxw == rw) {\n for (i = vbox.r1; i <= vbox.r2; i++) {\n sum = 0;\n\n for (j = vbox.g1; j <= vbox.g2; j++) {\n for (k = vbox.b1; k <= vbox.b2; k++) {\n index = getColorIndex(i, j, k);\n sum += histo[index] || 0;\n }\n }\n\n total += sum;\n partialsum[i] = total;\n }\n } else if (maxw == gw) {\n for (i = vbox.g1; i <= vbox.g2; i++) {\n sum = 0;\n\n for (j = vbox.r1; j <= vbox.r2; j++) {\n for (k = vbox.b1; k <= vbox.b2; k++) {\n index = getColorIndex(j, i, k);\n sum += histo[index] || 0;\n }\n }\n\n total += sum;\n partialsum[i] = total;\n }\n } else {\n /* maxw == bw */\n for (i = vbox.b1; i <= vbox.b2; i++) {\n sum = 0;\n\n for (j = vbox.r1; j <= vbox.r2; j++) {\n for (k = vbox.g1; k <= vbox.g2; k++) {\n index = getColorIndex(j, k, i);\n sum += histo[index] || 0;\n }\n }\n\n total += sum;\n partialsum[i] = total;\n }\n }\n\n partialsum.forEach(function (d, i) {\n lookaheadsum[i] = total - d;\n });\n\n function doCut(color) {\n var dim1 = color + '1',\n dim2 = color + '2',\n left,\n right,\n vbox1,\n vbox2,\n d2,\n count2 = 0;\n\n for (i = vbox[dim1]; i <= vbox[dim2]; i++) {\n if (partialsum[i] > total / 2) {\n vbox1 = vbox.copy();\n vbox2 = vbox.copy();\n left = i - vbox[dim1];\n right = vbox[dim2] - i;\n 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\n\n while (!partialsum[d2]) { d2++; }\n\n count2 = lookaheadsum[d2];\n\n while (!count2 && partialsum[d2 - 1]) { count2 = lookaheadsum[--d2]; } // set dimensions\n\n\n vbox1[dim2] = d2;\n vbox2[dim1] = vbox1[dim2] + 1; // console.log('vbox counts:', vbox.count(), vbox1.count(), vbox2.count());\n\n return [vbox1, vbox2];\n }\n }\n } // determine the cut planes\n\n\n return maxw == rw ? doCut('r') : maxw == gw ? doCut('g') : doCut('b');\n }\n\n function quantize(pixels, maxcolors) {\n // short-circuit\n if (!pixels.length || maxcolors < 2 || maxcolors > 256) {\n // console.log('wrong number of maxcolors');\n return false;\n } // XXX: check color content and convert to grayscale if insufficient\n\n\n var histo = getHisto(pixels);\n // check that we aren't below maxcolors already\n histo.forEach(function () {\n });\n // get the beginning vbox from the colors\n\n\n var vbox = vboxFromPixels(pixels, histo),\n pq = new PQueue(function (a, b) {\n return pv.naturalOrder(a.count(), b.count());\n });\n pq.push(vbox); // inner function to do the iteration\n\n function iter(lh, target) {\n var ncolors = lh.size(),\n niters = 0,\n vbox;\n\n while (niters < maxIterations) {\n if (ncolors >= target) { return; }\n\n if (niters++ > maxIterations) {\n // console.log(\"infinite loop; perhaps too few pixels!\");\n return;\n }\n\n vbox = lh.pop();\n\n if (!vbox.count()) {\n /* just put it back */\n lh.push(vbox);\n niters++;\n continue;\n } // do the cut\n\n\n var vboxes = medianCutApply(histo, vbox),\n vbox1 = vboxes[0],\n vbox2 = vboxes[1];\n\n if (!vbox1) {\n // console.log(\"vbox1 not defined; shouldn't happen!\");\n return;\n }\n\n lh.push(vbox1);\n\n if (vbox2) {\n /* vbox2 can be null */\n lh.push(vbox2);\n ncolors++;\n }\n }\n } // first set of colors, sorted by population\n\n\n iter(pq, fractByPopulations * maxcolors); // console.log(pq.size(), pq.debug().length, pq.debug().slice());\n // Re-sort by the product of pixel occupancy times the size in color space.\n\n var pq2 = new PQueue(function (a, b) {\n return pv.naturalOrder(a.count() * a.volume(), b.count() * b.volume());\n });\n\n while (pq.size()) {\n pq2.push(pq.pop());\n } // next set - generate the median cuts using the (npix * vol) sorting.\n\n\n iter(pq2, maxcolors); // calculate the actual colors\n\n var cmap = new CMap();\n\n while (pq2.size()) {\n cmap.push(pq2.pop());\n }\n\n return cmap;\n }\n\n return {\n quantize: quantize\n };\n}();\n\nvar quantize = MMCQ.quantize;\n\nexport default quantize;\n","import quantize from '../node_modules/quantize/dist/index.mjs';\n\n/*\n * Color Thief v2.2.0\n * by Lokesh Dhakar - http://www.lokeshdhakar.com\n *\n * Thanks\n * ------\n * Nick Rabinowitz - For creating quantize.js.\n * John Schulz - For clean up and optimization. @JFSIII\n * Nathan Spady - For adding drag and drop support to the demo page.\n *\n * License\n * -------\n * Copyright Lokesh Dhakar\n * Released under the MIT license\n * https://raw.githubusercontent.com/lokesh/color-thief/master/LICENSE\n *\n * @license\n */\n\n\n/*\n CanvasImage Class\n Class that wraps the html image element and canvas.\n It also simplifies some of the canvas context manipulation\n with a set of helper functions.\n*/\n\nvar CanvasImage = function (image) {\n this.canvas = document.createElement('canvas');\n this.context = this.canvas.getContext('2d');\n\n this.width = this.canvas.width = image.width;\n this.height = this.canvas.height = image.height;\n\n this.context.drawImage(image, 0, 0, this.width, this.height);\n};\n\nCanvasImage.prototype.getPixelCount = function () {\n return this.width * this.height;\n};\n\nCanvasImage.prototype.getImageData = function () {\n return this.context.getImageData(0, 0, this.width, this.height);\n};\n\nvar ColorThief = function () {};\n\n/*\n * getColor(sourceImage[, quality])\n * returns {r: num, g: num, b: num}\n *\n * Use the median cut algorithm provided by quantize.js to cluster similar\n * colors and return the base color from the largest cluster.\n *\n * Quality is an optional argument. It needs to be an integer. 1 is the highest quality settings.\n * 10 is the default. There is a trade-off between quality and speed. The bigger the number, the\n * faster a color will be returned but the greater the likelihood that it will not be the visually\n * most dominant color.\n *\n * */\nColorThief.prototype.getColor = function(sourceImage, quality) {\n var palette = this.getPalette(sourceImage, 5, quality);\n var dominantColor = palette[0];\n return dominantColor;\n};\n\n\n/*\n * getPalette(sourceImage[, colorCount, quality])\n * returns array[ {r: num, g: num, b: num}, {r: num, g: num, b: num}, ...]\n *\n * Use the median cut algorithm provided by quantize.js to cluster similar colors.\n *\n * colorCount determines the size of the palette; the number of colors returned. If not set, it\n * defaults to 10.\n *\n * BUGGY: Function does not always return the requested amount of colors. It can be +/- 2.\n *\n * quality is an optional argument. It needs to be an integer. 1 is the highest quality settings.\n * 10 is the default. There is a trade-off between quality and speed. The bigger the number, the\n * faster the palette generation but the greater the likelihood that colors will be missed.\n *\n *\n */\nColorThief.prototype.getPalette = function(sourceImage, colorCount, quality) {\n\n if (typeof colorCount === 'undefined' || colorCount < 2 || colorCount > 256) {\n colorCount = 10;\n }\n if (typeof quality === 'undefined' || quality < 1) {\n quality = 10;\n }\n\n // Create custom CanvasImage object\n var image = new CanvasImage(sourceImage);\n var imageData = image.getImageData();\n var pixels = imageData.data;\n var pixelCount = image.getPixelCount();\n\n // Store the RGB values in an array format suitable for quantize function\n var pixelArray = [];\n for (var i = 0, offset, r, g, b, a; i < pixelCount; i = i + quality) {\n offset = i * 4;\n r = pixels[offset + 0];\n g = pixels[offset + 1];\n b = pixels[offset + 2];\n a = pixels[offset + 3];\n // If pixel is mostly opaque and not white\n if (a >= 125) {\n if (!(r > 250 && g > 250 && b > 250)) {\n pixelArray.push([r, g, b]);\n }\n }\n }\n\n // Send array to quantize function which clusters values\n // using median cut algorithm\n var cmap = quantize(pixelArray, colorCount);\n var palette = cmap? cmap.palette() : null;\n\n return palette;\n};\n\nColorThief.prototype.getColorFromUrl = function(imageUrl, callback, quality) {\n let sourceImage = document.createElement(\"img\");\n var thief = this;\n sourceImage.addEventListener('load' , function(){\n var palette = thief.getPalette(sourceImage, 5, quality);\n var dominantColor = palette[0];\n callback(dominantColor, imageUrl);\n });\n sourceImage.src = imageUrl\n};\n\n\nColorThief.prototype.getImageData = function(imageUrl, callback) {\n let xhr = new XMLHttpRequest();\n xhr.open('GET', imageUrl, true);\n xhr.responseType = 'arraybuffer'\n xhr.onload = function() {\n if (this.status == 200) {\n let uInt8Array = new Uint8Array(this.response)\n i = uInt8Array.length\n let binaryString = new Array(i);\n for (var i = 0; i < uInt8Array.length; i++){\n binaryString[i] = String.fromCharCode(uInt8Array[i])\n }\n let data = binaryString.join('')\n let base64 = window.btoa(data)\n callback (\"data:image/png;base64,\"+base64)\n }\n }\n xhr.send();\n};\n\nColorThief.prototype.getColorAsync = function(imageUrl, callback, quality) {\n var thief = this;\n this.getImageData(imageUrl, function(imageData){\n let sourceImage = document.createElement(\"img\");\n sourceImage.addEventListener('load' , function(){\n var palette = thief.getPalette(sourceImage, 5, quality);\n var dominantColor = palette[0];\n callback(dominantColor, this);\n });\n sourceImage.src = imageData;\n });\n};\n\n\nexport default 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