Created
March 6, 2014 16:50
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http://charlesleifer.com/static/colors/ & http://charlesleifer.com/blog/using-python-and-k-means-to-find-the-dominant-colors-in-images/
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function euclidean(p1, p2) { | |
var s = 0; | |
for (var i = 0, l = p1.length; i < l; i++) { | |
s += Math.pow(p1[i] - p2[i], 2) | |
} | |
return Math.sqrt(s); | |
} | |
function calculateCenter(points, n) { | |
var vals = [] | |
, plen = 0; | |
for (var i = 0; i < n; i++) { vals.push(0); } | |
for (var i = 0, l = points.length; i < l; i++) { | |
plen++; | |
for (var j = 0; j < n; j++) { | |
vals[j] += points[i][j]; | |
} | |
} | |
for (var i = 0; i < n; i++) { | |
vals[i] = vals[i] / plen; | |
} | |
return vals; | |
} | |
function kmeans(points, k, min_diff) { | |
plen = points.length; | |
clusters = []; | |
seen = []; | |
while (clusters.length < k) { | |
idx = parseInt(Math.random() * plen); | |
found = false; | |
for (var i = 0; i < seen.length; i++ ) { | |
if (idx === seen[i]) { | |
found = true; | |
break; | |
} | |
} | |
if (!found) { | |
seen.push(idx); | |
clusters.push([points[idx], [points[idx]]]); | |
} | |
} | |
while (true) { | |
plists = []; | |
for (var i = 0; i < k; i++) { | |
plists.push([]); | |
} | |
for (var j = 0; j < plen; j++) { | |
var p = points[j] | |
, smallest_distance = 10000000 | |
, idx = 0; | |
for (var i = 0; i < k; i++) { | |
var distance = euclidean(p, clusters[i][0]); | |
if (distance < smallest_distance) { | |
smallest_distance = distance; | |
idx = i; | |
} | |
} | |
plists[idx].push(p); | |
} | |
var diff = 0; | |
for (var i = 0; i < k; i++) { | |
var old = clusters[i] | |
, list = plists[i] | |
, center = calculateCenter(plists[i], 3) | |
, new_cluster = [center, (plists[i])] | |
, dist = euclidean(old[0], center); | |
clusters[i] = new_cluster | |
diff = diff > dist ? diff : dist; | |
} | |
if (diff < min_diff) { | |
break; | |
} | |
} | |
return clusters; | |
} | |
function rgbToHex(rgb) { | |
function th(i) { | |
var h = parseInt(i).toString(16); | |
return h.length == 1 ? '0'+h : h; | |
} | |
return '#' + th(rgb[0]) + th(rgb[1]) + th(rgb[2]); | |
} | |
function process_image(img, ctx) { | |
var points = []; | |
ctx.drawImage(img, 0, 0, 200, 200); | |
data = ctx.getImageData(0, 0, 200, 200).data; | |
for (var i = 0, l = data.length; i < l; i += 4) { | |
var r = data[i] | |
, g = data[i+1] | |
, b = data[i+2]; | |
points.push([r, g, b]); | |
} | |
var results = kmeans(points, 3, 1) | |
, hex = []; | |
for (var i = 0; i < results.length; i++) { | |
hex.push(rgbToHex(results[i][0])); | |
} | |
return hex; | |
} | |
function analyze(img_elem) { | |
var ctx = document.getElementById('canvas').getContext('2d') | |
, img = new Image(); | |
img.onload = function() { | |
var results = document.getElementById('results'); | |
results.innerHTML = 'Waiting...'; | |
var colors = process_image(img, ctx) | |
, p1 = document.getElementById('c1') | |
, p2 = document.getElementById('c2') | |
, p3 = document.getElementById('c3'); | |
p1.style.backgroundColor = colors[0]; | |
p2.style.backgroundColor = colors[1]; | |
p3.style.backgroundColor = colors[2]; | |
results.innerHTML = 'Done'; | |
} | |
img.src = img_elem.src; | |
} |
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