"""simple docstring"""
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey



class 	lowerCAmelCase_     :



				"""simple docstring"""

				def __init__(					self		,     lowerCAmelCase		,     lowerCAmelCase     ):






										"""simple docstring"""

										snake_case             =      0
										# max greyscale value for #FFFFFF
										snake_case             =      int(self.get_greyscale(2_55		,     2_55		,     2_55     )     )

										if not self.min_threshold < threshold < self.max_threshold:
																snake_case             =      F"""Factor value should be from 0 to {self.max_threshold}"""
																raise ValueError(A__     )

										snake_case             =      input_img
										snake_case             =      threshold
										snake_case       ,snake_case             =      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
										snake_case             =      [
										    [0 for _ in range(self.height + 4     )] for __ in range(self.width + 1     )
										]
										snake_case             =      np.ones((self.width, self.height, 3)		,     np.uinta     ) * 2_55

				@classmethod
				def 		snake_case			(					cls		,     lowerCAmelCase		,     lowerCAmelCase		,     lowerCAmelCase     ):






										"""simple docstring"""

										return 0.1_14 * blue + 0.5_87 * green + 0.21_26 * red

				def 		snake_case			(					self     ):






										"""simple docstring"""

										for y in range(self.height     ):
																for x in range(self.width     ):
																						snake_case             =      int(self.get_greyscale(*self.input_img[y][x]     )     )
																						if self.threshold > greyscale + self.error_table[y][x]:
																												snake_case             =      (0, 0, 0)
																												snake_case             =      greyscale + self.error_table[x][y]
																						else:
																												snake_case             =      (2_55, 2_55, 2_55)
																												snake_case             =      greyscale + self.error_table[x][y] - 2_55
																						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__       =	[
					    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()








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






class       A      :
     """simple docstring"""

     def __init__(     self	: int						,	A__	: List[Any]						,	A__	: int      )					->							List[str]:
           lowerCamelCase__   	=					0
           # max greyscale value for #FFFFFF
           lowerCamelCase__   	=					int(self.get_greyscale(2_5_5						,	2_5_5						,	2_5_5      )      )

           if not self.min_threshold < threshold < self.max_threshold:
                 lowerCamelCase__   	=					F"""Factor value should be from 0 to {self.max_threshold}"""
                 raise ValueError(A__      )

           lowerCamelCase__   	=					input_img
           lowerCamelCase__   	=					threshold
           lowerCamelCase__	,		lowerCamelCase__   	=					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__   	=					[
               [0 for _ in range(self.height + 4      )] for __ in range(self.width + 1      )
           ]
           lowerCamelCase__   	=					np.ones((self.width, self.height, 3)						,	np.uinta      ) * 2_5_5




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




     def 			__snake_case (     self	: List[Any]      )					->							None:
           for y in range(self.height      ):
                 for x in range(self.width      ):
                       lowerCamelCase__   	=					int(self.get_greyscale(*self.input_img[y][x]      )      )
                       if self.threshold > greyscale + self.error_table[y][x]:
                             lowerCamelCase__   	=					(0, 0, 0)
                             lowerCamelCase__   	=					greyscale + self.error_table[x][y]
                       else:
                             lowerCamelCase__   	=					(2_5_5, 2_5_5, 2_5_5)
                             lowerCamelCase__   	=					greyscale + self.error_table[x][y] - 2_5_5
                       self.error_table[y][x + 1] += int(8 / 3_2 * current_error      )
                       self.error_table[y][x + 2] += int(4 / 3_2 * current_error      )
                       self.error_table[y + 1][x] += int(8 / 3_2 * current_error      )
                       self.error_table[y + 1][x + 1] += int(4 / 3_2 * current_error      )
                       self.error_table[y + 1][x + 2] += int(2 / 3_2 * current_error      )
                       self.error_table[y + 1][x - 1] += int(4 / 3_2 * current_error      )
                       self.error_table[y + 1][x - 2] += int(2 / 3_2 * current_error      )


if __name__ == "__main__":
      # create Burke's instances with original images in greyscale
      __SCREAMING_SNAKE_CASE     : Optional[Any]      =[
          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()