code: def _calc_colour_hist(img):
      
  
      BINS = 25
      hist = numpy.array([])
  
      for colour_channel in (0, 1, 2):
  
          # extracting one colour channel
          c = img[:, colour_channel]
  
          # calculate histogram for each colour and join to the result
          hist = numpy.concatenate(
              [hist] + [numpy.histogram(c, BINS, (0.0, 255.0))[0]])
  
      # L1 normalize
      hist = hist / len(img)
  
      return hist
docs: calculate colour histogram for each region
  
          the size of output histogram will be BINS * COLOUR_CHANNELS(3)
  
          number of bins is 25 as same as [uijlings_ijcv2013_draft.pdf]
  
          extract HSV