text: from __future__ import print_function
  from __future__ import division
  import cv2 as cv
  import numpy as np
  import argparse
  
  ## [Load image]
  parser = argparse.ArgumentParser(description='Code for Histogram Calculation tutorial.')
  parser.add_argument('--input', help='Path to input image.', default='lena.jpg')
  args = parser.parse_args()
  
  src = cv.imread(cv.samples.findFile(args.input))
  if src is None:
      print('Could not open or find the image:', args.input)
      exit(0)
  ## [Load image]
  
  ## [Separate the image in 3 places ( B, G and R )]
  bgr_planes = cv.split(src)
  ## [Separate the image in 3 places ( B, G and R )]
  
  ## [Establish the number of bins]
  histSize = 256
  ## [Establish the number of bins]
  
  ## [Set the ranges ( for B,G,R) )]
  histRange = (0, 256) # the upper boundary is exclusive
  ## [Set the ranges ( for B,G,R) )]
  
  ## [Set histogram param]
  accumulate = False
  ## [Set histogram param]
  
  ## [Compute the histograms]
  b_hist = cv.calcHist(bgr_planes, [0], None, [histSize], histRange, accumulate=accumulate)
  g_hist = cv.calcHist(bgr_planes, [1], None, [histSize], histRange, accumulate=accumulate)
  r_hist = cv.calcHist(bgr_planes, [2], None, [histSize], histRange, accumulate=accumulate)
  ## [Compute the histograms]
  
  ## [Draw the histograms for B, G and R]
  hist_w = 512
  hist_h = 400
  bin_w = int(round( hist_w/histSize ))
  
  histImage = np.zeros((hist_h, hist_w, 3), dtype=np.uint8)
  ## [Draw the histograms for B, G and R]
  
  ## [Normalize the result to ( 0, histImage.rows )]
  cv.normalize(b_hist, b_hist, alpha=0, beta=hist_h, norm_type=cv.NORM_MINMAX)
  cv.normalize(g_hist, g_hist, alpha=0, beta=hist_h, norm_type=cv.NORM_MINMAX)
  cv.normalize(r_hist, r_hist, alpha=0, beta=hist_h, norm_type=cv.NORM_MINMAX)
  ## [Normalize the result to ( 0, histImage.rows )]
  
  ## [Draw for each channel]
  for i in range(1, histSize):
      cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(b_hist[i-1])) ),
              ( bin_w*(i), hist_h - int(round(b_hist[i])) ),
              ( 255, 0, 0), thickness=2)
      cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(g_hist[i-1])) ),
              ( bin_w*(i), hist_h - int(round(g_hist[i])) ),
              ( 0, 255, 0), thickness=2)
      cv.line(histImage, ( bin_w*(i-1), hist_h - int(round(r_hist[i-1])) ),
              ( bin_w*(i), hist_h - int(round(r_hist[i])) ),
              ( 0, 0, 255), thickness=2)
  ## [Draw for each channel]
  
  ## [Display]
  cv.imshow('Source image', src)
  cv.imshow('calcHist Demo', histImage)
  cv.waitKey()
  ## [Display]
  