text: # import numpy as np
  # import cv2
  
  # # Load an color image in grayscale
  # # img = cv2.imread('assets\messi.jpg',0)
  # # scale_percent =25  # percent of original size
  # # width = int(img.shape[1] * scale_percent / 100)
  # # height = int(img.shape[0] * scale_percent / 100)
  # # dim = (width, height)
    
  # # # resize image
  # # resized = cv2.resize(img, dim, interpolation = cv2.INTER_AREA)
  # # cv2.imshow('image',resized)
  # # cv2.imwrite('messigray.png',resized)
  # # cv2.waitKey(0)
  # # cv2.destroyAllWindows()
  
  
  
  # img = cv2.imread('assets\messi.jpg',0)
  # cv2.imshow('image',img)
  # k = cv2.waitKey(0) & 0xFF
  # if k == 27:         # wait for ESC key to exit
  #     cv2.destroyAllWindows()
  # elif k == ord('s'): # wait for 's' key to save and exit
  #     cv2.imwrite('messigray.png',img)
  #     cv2.destroyAllWindows()
      
      
      
      
  
  
  # import numpy as np
  # import cv2
  # from matplotlib import pyplot as plt
  
  # img = cv2.imread('assets\messi.jpg',-1)
  # im_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
  # plt.imshow(im_rgb, cmap = 'gray', interpolation = 'bicubic')
  # plt.xticks([]), plt.yticks([])  # to hide tick values on X and Y axis
  # plt.show()
  
  import numpy as np
  import matplotlib.pyplot as plt
  
  x = np.arange(0, 5, 0.1);
  y = np.sin(x)
  plt.plot(x, y)