





'''simple docstring'''






import random







class 		UpperCAmelCase   :


  """simple docstring"""







  @staticmethod
  def   UpperCamelCase__      (				UpperCamelCase__    :					List[str]  )     ->						Optional[Any]:
    _UpperCamelCase       			=[ord(snake_case__  ) for i in text]
    _UpperCamelCase       			=[]
    _UpperCamelCase       			=[]
    for i in plain:
      _UpperCamelCase       			=random.randint(1							,	300  )
      _UpperCamelCase       			=(i + k) * k
      cipher.append(snake_case__  )
      key.append(snake_case__  )
    return cipher, key




  @staticmethod
  def   UpperCamelCase__      (				UpperCamelCase__    :					Dict							,	UpperCamelCase__    :					str  )     ->						Any:
    _UpperCamelCase       			=[]
    for i in range(len(snake_case__  )  ):
      _UpperCamelCase       			=int((cipher[i] - (key[i]) ** 2) / key[i]  )
      plain.append(chr(snake_case__  )  )
    return "".join(snake_case__  )


if __name__ == "__main__":
      __lowerCamelCase						: Optional[Any]		=   Onepad().encrypt('Hello')
      print(c, k)
      print(Onepad().decrypt(c, k))













'''simple docstring'''






from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt


def 					_a   (__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  _UpperCamelCase       			=cva.getAffineTransform(__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   )
  return cva.warpAffine(__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      (rows, cols)   )


if __name__ == "__main__":
      # read original image
      __lowerCamelCase						: List[Any]		=   cva.imread(
          str(Path(__file__).resolve().parent.parent / 'image_data' / 'lena.jpg')
      )
      # turn image in gray scale value
      __lowerCamelCase						: List[Any]		=   cva.cvtColor(image, cva.COLOR_BGR2GRAY)
      # get image shape
      __lowerCamelCase		, __lowerCamelCase						: Any		=   gray_img.shape

      # set different points to rotate image
      __lowerCamelCase						: Optional[Any]		=   np.array([[50, 50], [200, 50], [50, 200]], np.floataa)
      __lowerCamelCase						: Any		=   np.array([[10, 100], [200, 50], [100, 250]], np.floataa)
      __lowerCamelCase						: int		=   np.array([[50, 50], [150, 50], [120, 200]], np.floataa)
      __lowerCamelCase						: List[Any]		=   np.array([[10, 100], [80, 50], [180, 250]], np.floataa)

      # add all rotated images in a list
      __lowerCamelCase						: int		=   [
          gray_img,
          get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
          get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
          get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
      ]

      # plot different image rotations
      __lowerCamelCase						: Optional[Any]		=   plt.figure(1)
      __lowerCamelCase						: Tuple		=   ['Original', 'Rotation 1', 'Rotation 2', 'Rotation 3']
      for i, image in enumerate(images):
            plt.subplot(2, 2, i + 1), plt.imshow(image, 'gray')
            plt.title(titles[i])
            plt.axis('off')
            plt.subplots_adjust(left=0.0, bottom=0.0_5, right=1.0, top=0.9_5)
      plt.show()






