text: import cv2 as cv
  import numpy as np
  import time
  
  start_time = time.time()
  
  FILE = './src/media/image9.jpg'
  SCALE_PERCENT = 10  # percent of original size
  
  # Import test image
  original = cv.imread(FILE, cv.IMREAD_UNCHANGED)
  original_RGB = cv.cvtColor(original, cv.COLOR_BGR2RGB)
  
  # Import image as greyscale
  greyscale_img = cv.imread(FILE, cv.IMREAD_GRAYSCALE)
  
  # resize image
  width = int(greyscale_img.shape[1] * SCALE_PERCENT / 100)
  height = int(greyscale_img.shape[0] * SCALE_PERCENT / 100)
  dim = (width, height)
  
  resized_original_img = cv.resize(
      original_RGB, dim, interpolation=cv.INTER_AREA)
  resized_greyscale_img = cv.resize(
      greyscale_img, dim, interpolation=cv.INTER_AREA)
  
  blur = cv.GaussianBlur(resized_greyscale_img, (5, 5), 0)
  ret3, th3 = cv.threshold(blur, 0, 255, cv.THRESH_BINARY+cv.THRESH_OTSU)
  
  # plot all the images and their histograms
  object_pixels = []
  for i in range(th3.shape[0]):
      for j in range(th3.shape[1]):
          if(th3[i][j] == 0):
              object_pixels.append(resized_original_img[i][j])
  
  a = np.asarray(object_pixels)
  unique_colors, count = np.unique(a,  axis=0,  return_counts=True)
  dom_color = unique_colors[count.argmax()]
  hexcode = '{:02x}{:02x}{:02x}'.format(
      dom_color[0], dom_color[1], dom_color[2])
  
  print('rgb', dom_color)
  print('File: {} | {}'.format(FILE, hexcode))
  print("--- %s s to process ---" % (time.time() - start_time))
  