text: 
  # python David_1_7_1_bilateral.py --image "../../../CV-PyImageSearch Gurus Course/Dataset/data/family.jpg"
  
  
  # 1.Preprocessing
      # import the necessary packages
  import argparse
  import cv2
  
      ## construct the argument parser and parse the arguments
  ap = argparse.ArgumentParser()
  ap.add_argument("-i", "--image", required=True, help="Path to the image")
  args = vars(ap.parse_args())
  
      ## load the image, display it, and construct the list of bilateral
  # filtering parameters that we are going to explore
  image = cv2.imread(args["image"])
  image = cv2.resize(image,(450,300), interpolation = cv2.INTER_CUBIC)
  cv2.imshow("Original", image)
  
  
  
  # 2.Define the Filter 
      ## 2.1 Suppose we have N(4) filter 
  filters = [(10,30,20),(20,60,40),(30,90,60),(50,150,100)]
  
  for (diameter, sigmaColor, sigmaSpace) in filters:  # for (list中某項裡面多個參數)
      blurred = cv2.bilateralFilter(image, diameter, sigmaColor, sigmaSpace)  
      title = "Blurred A={}, B={}, C={}".format(diameter, sigmaColor, sigmaSpace)
      cv2.imshow(title, blurred)
      cv2.waitKey(0)
  
  # params = [ (11, 41, 21), (11, 61, 39), (11, 100, 60),]
  
  # # loop over the diameter, sigma color, and sigma space
  # for (diameter, sigmaColor, sigmaSpace) in params:
  # 	# apply bilateral filtering and display the image
  # 	blurred = cv2.bilateralFilter(image, diameter, sigmaColor, sigmaSpace)
  # 	title = "Blurred d={}, sc={}, ss={}".format(diameter, sigmaColor, sigmaSpace)
  # 	cv2.imshow(title, blurred)
  # 	cv2.waitKey(0)
  
  
  
  