{"id":156045,"date":"2012-10-25T03:08:04","date_gmt":"2012-10-24T23:08:04","guid":{"rendered":"http:\/\/savepearlharbor.com\/?p=156045"},"modified":"-0001-11-30T00:00:00","modified_gmt":"-0001-11-29T21:00:00","slug":"","status":"publish","type":"post","link":"https:\/\/savepearlharbor.com\/?p=156045","title":{"rendered":"\u041e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435 \u0434\u043e\u043c\u0438\u043d\u0438\u0440\u0443\u044e\u0449\u0438\u0445 \u0446\u0432\u0435\u0442\u043e\u0432: Python \u0438 \u043c\u0435\u0442\u043e\u0434 k-\u0441\u0440\u0435\u0434\u043d\u0438\u0445<\/span>"},"content":{"rendered":"
\t
\u00a9Assorium<\/a><\/sup><\/p>\n

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<\/a>
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\u0412 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0435 \u043f\u043e\u043b\u0443\u0447\u0430\u0435\u0442\u0441\u044f \u043f\u0440\u0438\u043c\u0435\u0440\u043d\u043e \u0442\u0430\u043a\u0430\u044f \u043a\u0430\u0440\u0442\u0438\u043d\u0430. \u0422\u043e\u0447\u043a\u0438 \u0440\u0430\u0441\u043a\u0440\u0430\u0448\u0435\u043d\u044b, \u0432 \u0437\u0430\u0432\u0438\u0441\u0438\u043c\u043e\u0441\u0442\u0438 \u043e\u0442 \u0446\u0432\u0435\u0442\u0430 \u043a\u043b\u0430\u0441\u0442\u0435\u0440\u0430, \u0447\u0451\u0440\u043d\u044b\u0435 \u0442\u043e\u0447\u043a\u0438 \u043e\u0442\u043e\u0431\u0440\u0430\u0436\u0430\u044e\u0442 \u0446\u0435\u043d\u0442\u0440\u044b \u043c\u0430\u0441\u0441.<\/p>\n

<\/p>\n

\u0412 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u0435 \u041b\u0435\u0439\u0444\u0435\u0440\u0430 \u043a\u0430\u0436\u0434\u0430\u044f \u0442\u043e\u0447\u043a\u0430 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u044f \u043f\u043e\u0437\u0438\u0446\u0438\u043e\u043d\u0438\u0440\u0443\u0435\u0442\u0441\u044f \u0432 \u0442\u0440\u0451\u0445\u043c\u0435\u0440\u043d\u043e\u043c \u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0441\u0442\u0432\u0435 RGB, \u0433\u0434\u0435 \u0438 \u0432\u044b\u0447\u0438\u0441\u043b\u044f\u0435\u0442\u0441\u044f \u0440\u0430\u0441\u0441\u0442\u043e\u044f\u043d\u0438\u0435 \u0434\u043e \u0446\u0435\u043d\u0442\u0440\u043e\u0432 \u043c\u0430\u0441\u0441. \u0414\u043b\u044f \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0438 \u043a\u0430\u0436\u0434\u0430\u044f \u043a\u0430\u0440\u0442\u0438\u043d\u043a\u0430 \u0443\u043c\u0435\u043d\u044c\u0448\u0430\u0435\u0442\u0441\u044f \u0434\u043e 200\u0445200 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 PIL<\/a>. \u041e\u043d\u0430 \u0436\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442\u0441\u044f \u0434\u043b\u044f \u0438\u0437\u0432\u043b\u0435\u0447\u0435\u043d\u0438\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 RGB. <\/p>\n

\u041a\u043e\u0434<\/b><\/p>\n
\n
 from collections import namedtuple from math import sqrt import random try:     import Image except ImportError:     from PIL import Image  Point = namedtuple('Point', ('coords', 'n', 'ct')) Cluster = namedtuple('Cluster', ('points', 'center', 'n'))  def get_points(img):     points = []     w, h = img.size     for count, color in img.getcolors(w * h):         points.append(Point(color, 3, count))     return points  rtoh = lambda rgb: '#%s' % ''.join(('%02x' % p for p in rgb))  def colorz(filename, n=3):     img = Image.open(filename)     img.thumbnail((200, 200))     w, h = img.size      points = get_points(img)     clusters = kmeans(points, n, 1)     rgbs = [map(int, c.center.coords) for c in clusters]     return map(rtoh, rgbs)  def euclidean(p1, p2):     return sqrt(sum([         (p1.coords[i] - p2.coords[i]) ** 2 for i in range(p1.n)     ]))  def calculate_center(points, n):     vals = [0.0 for i in range(n)]     plen = 0     for p in points:         plen += p.ct         for i in range(n):             vals[i] += (p.coords[i] * p.ct)     return Point([(v \/ plen) for v in vals], n, 1)  def kmeans(points, k, min_diff):     clusters = [Cluster([p], p, p.n) for p in random.sample(points, k)]      while 1:         plists = [[] for i in range(k)]          for p in points:             smallest_distance = float('Inf')             for i in range(k):                 distance = euclidean(p, clusters[i].center)                 if distance < smallest_distance:                     smallest_distance = distance                     idx = i             plists[idx].append(p)          diff = 0         for i in range(k):             old = clusters[i]             center = calculate_center(plists[i], old.n)             new = Cluster(plists[i], center, old.n)             clusters[i] = new             diff = max(diff, euclidean(old.center, new.center))          if diff < min_diff:             break      return clusters<\/code><\/pre>\n<\/div>\n<\/div>\n
  \u041f\u0440\u0438\u043c\u0435\u0440\u044b<\/p>\n
   
  \u0420\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442: <\/p>\n
  
  \u0420\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442: <\/p>\n
  
  \u0420\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442: <\/p>\n
  
  \u0420\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442: <\/p>\n
  \u041e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u0435 \u0434\u043e\u043c\u0438\u043d\u0438\u0440\u0443\u044e\u0449\u0438\u0445 \u0446\u0432\u0435\u0442\u043e\u0432 \u2014 \u0434\u043e\u0432\u043e\u043b\u044c\u043d\u043e \u043f\u043e\u043b\u0435\u0437\u043d\u0430\u044f \u0432\u0435\u0449\u044c, \u043a\u043e\u0442\u043e\u0440\u043e\u0439 \u0432\u0441\u0435\u0433\u0434\u0430 \u043d\u0430\u0439\u0434\u0451\u0442\u0441\u044f \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435. \u042d\u0442\u043e \u0432\u044b\u0431\u043e\u0440 \u043f\u0430\u043b\u0438\u0442\u0440\u044b \u0434\u043b\u044f \u0432\u0435\u0431-\u0441\u0430\u0439\u0442\u0430 \u0438\u043b\u0438 \u043d\u0435\u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u044d\u043b\u0435\u043c\u0435\u043d\u0442\u043e\u0432 UI. \u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0431\u0440\u0430\u0443\u0437\u0435\u0440 Chrome \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442<\/a> \u043c\u0435\u0442\u043e\u0434 k-\u0441\u0440\u0435\u0434\u043d\u0438\u0445 \u0434\u043b\u044f \u0432\u044b\u0431\u043e\u0440\u0430 \u0434\u043e\u043c\u0438\u043d\u0438\u0440\u0443\u044e\u0449\u0435\u0433\u043e \u0446\u0432\u0435\u0442\u0430 \u0441 \u0444\u0430\u0432\u0438\u043a\u043e\u043d\u0430.<\/p>\n
      \t   \t<\/p>\n
<\/div>\n<\/p><\/div>\n
 \u0441\u0441\u044b\u043b\u043a\u0430 \u043d\u0430 \u043e\u0440\u0438\u0433\u0438\u043d\u0430\u043b \u0441\u0442\u0430\u0442\u044c\u0438  http:\/\/habrahabr.ru\/post\/156045\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
   \t
  \u00a9Assorium<\/a><\/sup><\/p>\n
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