




import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey




class 	UpperCamelCase__			:

    '''simple docstring'''



    def __init__(					self  ,						UpperCamelCase__  ,						UpperCamelCase__  )  ->   Any:
           lowerCamelCase     :   Optional[Any]    				=      0
           # max greyscale value for #FFFFFF
           lowerCamelCase     :   str    				=      int(self.get_greyscale(255  ,						255  ,						255  )  )

           if not self.min_threshold < threshold < self.max_threshold:
                  lowerCamelCase     :   Dict    				=      F'''Factor value should be from 0 to {self.max_threshold}'''
                  raise ValueError(UpperCamelCase__  )

           lowerCamelCase     :   Optional[Any]    				=      input_img
           lowerCamelCase     :   List[Any]    				=      threshold
           lowerCamelCase				,   lowerCamelCase     :   str    				=      self.input_img.shape[1], self.input_img.shape[0]

           # error table size (+4 columns and +1 row) greater than input image because of
           # lack of if statements
           lowerCamelCase     :   Any    				=      [
               [0 for _ in range(self.height + 4  )] for __ in range(self.width + 1  )
           ]
           lowerCamelCase     :   List[Any]    				=      np.ones((self.width, self.height, 3)  ,						np.uinta  ) * 255







    @classmethod
    def 					_lowercase  (					cls  ,						UpperCamelCase__  ,						UpperCamelCase__  ,						UpperCamelCase__  )  ->   float:
           return 0.114 * blue + 0.587 * green + 0.2126 * red







    def 					_lowercase  (					self  )  ->   None:
           for y in range(self.height  ):
                  for x in range(self.width  ):
                         lowerCamelCase     :   Dict    				=      int(self.get_greyscale(*self.input_img[y][x]  )  )
                         if self.threshold > greyscale + self.error_table[y][x]:
                                lowerCamelCase     :   Tuple    				=      (0, 0, 0)
                                lowerCamelCase     :   Any    				=      greyscale + self.error_table[x][y]
                         else:
                                lowerCamelCase     :   List[Any]    				=      (255, 255, 255)
                                lowerCamelCase     :   Any    				=      greyscale + self.error_table[x][y] - 255
                         self.error_table[y][x + 1] += int(8 / 32 * current_error  )
                         self.error_table[y][x + 2] += int(4 / 32 * current_error  )
                         self.error_table[y + 1][x] += int(8 / 32 * current_error  )
                         self.error_table[y + 1][x + 1] += int(4 / 32 * current_error  )
                         self.error_table[y + 1][x + 2] += int(2 / 32 * current_error  )
                         self.error_table[y + 1][x - 1] += int(4 / 32 * current_error  )
                         self.error_table[y + 1][x - 2] += int(2 / 32 * current_error  )


if __name__ == "__main__":
       # create Burke's instances with original images in greyscale
       SCREAMING_SNAKE_CASE__ :   Dict						=     [
           Burkes(imread('image_data/lena.jpg', 1), threshold)
           for threshold in (1, 126, 130, 140)
       ]

       for burkes in burkes_instances:
              burkes.process()

       for burkes in burkes_instances:
              imshow(
                  f'''Original image with dithering threshold: {burkes.threshold}''',
                  burkes.output_img,
              )

       waitKey(0)
       destroyAllWindows()












from __future__ import annotations

def   A   (   _SCREAMING_SNAKE_CASE					)			->				list[int]:
       assert (
           isinstance(_SCREAMING_SNAKE_CASE				,_SCREAMING_SNAKE_CASE					) and mask > 0
       ), f'''mask needs to be positive integer, your input {mask}'''
       lowerCamelCase     :   str    				=      []
       lowerCamelCase     :   Any    				=      mask

       while submask:
              all_submasks.append(_SCREAMING_SNAKE_CASE					)
              lowerCamelCase     :   Union[str, Any]    				=      (submask - 1) & mask

       return all_submasks


if __name__ == "__main__":
       import doctest

       doctest.testmod()






