text: # import the necessary packages
  import numpy as np
  import cv2
  
  def centroid_histogram(clt):
  	# grab the number of different clusters and create a histogram
  	# based on the number of pixels assigned to each cluster
  	numLabels = np.arange(0, len(np.unique(clt.labels_)) + 1)
  	(hist, _) = np.histogram(clt.labels_, bins = numLabels)
  
  	# normalize the histogram, such that it sums to one
  	hist = hist.astype("float")
  	hist /= hist.sum()
  
  	# return the histogram
  	return hist
  
  def plot_colors(hist, centroids):
  	# initialize the bar chart representing the relative frequency
  	# of each of the colors
  	bar = np.zeros((50, 300, 3), dtype = "uint8")
  	startX = 0
  
  	# loop over the percentage of each cluster and the color of
  	# each cluster
  	for (percent, color) in zip(hist, centroids):
  		# plot the relative percentage of each cluster
  		endX = startX + (percent * 300)
  		cv2.rectangle(bar, (int(startX), 0), (int(endX), 50),
  			color.astype("uint8").tolist(), -1)
  		startX = endX
  	
  	# return the bar chart
  	return bar