我正在学习使用quantitize.js ，但收到错误“Uncaught TypeError: Object # has no method 'palette'”。我不知道出了什么问题。请帮忙。谢谢。
这是代码：
<div></div>
<script
src="jquery-2.0.3.min.js"></script>
<script>
/*!
* quantize.js Copyright 2008 Nick Rabinowitz.
* Licensed under the MIT license: http://www.opensource.org/licenses/mit-license.php
*/
// 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
*/
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,
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 && rval <= vbox.g2 &&
bval >= vbox.b1 && rval <= 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 < vboxes.size(); i++) {
if (vboxes.peek(i).vbox.contains(color)) {
return vboxes.peek(i).color;
}
}
return this.nearest(color);
},
nearest: function (color) {
var vboxes = this.vboxes,
d1, d2, pColor;
for (var i = 0; i < vboxes.size(); i++) {
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[1] - vboxes.peek(i).color[1], 2)
);
if (d2 < d1 || d1 === undefined) {
d1 = d2;
pColor = vboxes.peek(i).color;
}
}
return pColor;
},
forcebw: function () {
// XXX: won't work yet
var vboxes = this.vboxes;
vboxes.sort(function (a, b) {
return pv.naturalOrder(pv.sum(a.color), pv.sum(b.color))
});
// force darkest color to black if everything < 5
var lowest = vboxes[0].color;
if (lowest[0] < 5 && lowest[1] < 5 && lowest[2] < 5)
vboxes[0].color = [0, 0, 0];
// force lightest color to white if everything > 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
}
})();
</script>
代码来自 quantitize.js。非常感谢。