code: import cv2
  import numpy as np
  import time
  
  
  # A required callback method that goes into the trackbar function.
  def nothing(x):
      pass
  
  
  # Initializing the webcam feed.
  cap = cv2.VideoCapture(0)
  cap.set(3, 1280)
  cap.set(4, 720)
  
  # Create a window named trackbars.
  cv2.namedWindow("Trackbars")
  
  # Now create 6 trackbars that will control the lower and upper range of
  # H,S and V channels. The Arguments are like this: Name of trackbar,
  # window name, range,callback function. For Hue the range is 0-179 and
  # for S,V its 0-255.
  cv2.createTrackbar("L - H", "Trackbars", 0, 179, nothing)
  cv2.createTrackbar("L - S", "Trackbars", 0, 255, nothing)
  cv2.createTrackbar("L - V", "Trackbars", 0, 255, nothing)
  cv2.createTrackbar("U - H", "Trackbars", 179, 179, nothing)
  cv2.createTrackbar("U - S", "Trackbars", 255, 255, nothing)
  cv2.createTrackbar("U - V", "Trackbars", 255, 255, nothing)
  
  while True:
  
      # Start reading the webcam feed frame by frame.
      ret, frame = cap.read()
      if not ret:
          break
      # Flip the frame horizontally (Not required)
      frame = cv2.flip(frame, 1)
  
      # Convert the BGR image to HSV image.
      hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
  
      # Get the new values of the trackbar in real time as the user changes
      # them
      l_h = cv2.getTrackbarPos("L - H", "Trackbars")
      l_s = cv2.getTrackbarPos("L - S", "Trackbars")
      l_v = cv2.getTrackbarPos("L - V", "Trackbars")
      u_h = cv2.getTrackbarPos("U - H", "Trackbars")
      u_s = cv2.getTrackbarPos("U - S", "Trackbars")
      u_v = cv2.getTrackbarPos("U - V", "Trackbars")
  
      # Set the lower and upper HSV range according to the value selected
      # by the trackbar
      lower_range = np.array([l_h, l_s, l_v])
      upper_range = np.array([u_h, u_s, u_v])
  
      # Filter the image and get the binary mask, where white represents
      # your target color
      mask = cv2.inRange(hsv, lower_range, upper_range)
  
      # You can also visualize the real part of the target color (Optional)
      res = cv2.bitwise_and(frame, frame, mask=mask)
  
      # Converting the binary mask to 3 channel image, this is just so
      # we can stack it with the others
      mask_3 = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
  
      # stack the mask, orginal frame and the filtered result
      stacked = np.hstack((mask_3, frame, res))
  
      # Show this stacked frame at 40% of the size.
      cv2.imshow('Trackbars', cv2.resize(stacked, None, fx=0.4, fy=0.4))
  
      # If the user presses ESC then exit the program
      key = cv2.waitKey(1)
      if key == 27:
          break
  
      # If the user presses `s` then print this array.
      if key == ord('s'):
  
          thearray = [[l_h, l_s, l_v], [u_h, u_s, u_v]]
          print(thearray)
  
          # Also save this array as penval.npy
          np.save('penval', thearray)
          break
  
  # Release the camera & destroy the windows.
  cap.release()
  cv2.destroyAllWindows()
apis: numpy.array numpy.save numpy.hstack