code: 
  
  
  
  
  """simple docstring"""
  
  import math
  import os
  
  import cva
  import numpy as np
  
  __A 		=			255.0
  
  
  
  def   UpperCamelCase__     (		lowercase__  :     float       ,     lowercase__  :     float   ):
    snake_case		:						Tuple								=				np.mean((original - contrast) ** 2   )
    if mse == 0:
      return 100
  
    return 20 * math.logaa(PIXEL_MAX / math.sqrt(lowercase__   )   )
  
  
  
  def   UpperCamelCase__     (		):
    snake_case		:						Union[str, Any]								=				os.path.dirname(os.path.realpath(lowercase__   )   )
    # Loading images (original image and compressed image)
    snake_case		:						int								=				cva.imread(os.path.join(lowercase__       ,     "image_data/original_image.png"   )   )
    snake_case		:						List[Any]								=				cva.imread(os.path.join(lowercase__       ,     "image_data/compressed_image.png"   )       ,     1   )
  
    snake_case		:						int								=				cva.imread(os.path.join(lowercase__       ,     "image_data/PSNR-example-base.png"   )   )
    snake_case		:						Optional[int]								=				cva.imread(
        os.path.join(lowercase__       ,     "image_data/PSNR-example-comp-10.jpg"   )       ,     1   )
  
    # Value expected: 29.73dB
    print("-- First Test --"   )
    print(F'''PSNR value is {peak_signal_to_noise_ratio(lowercase__       ,     lowercase__   )} dB'''   )
  
    # # Value expected: 31.53dB (Wikipedia Example)
    print("\n-- Second Test --"   )
    print(F'''PSNR value is {peak_signal_to_noise_ratio(lowercase__       ,     lowercase__   )} dB'''   )
  
  
  if __name__ == "__main__":
         main()
  
  
style_context: 
  
  
  
  
  """simple docstring"""
  
  import numpy as np
  from cva import destroyAllWindows, imread, imshow, waitKey
  class 			lowerCamelCase__    :
  
  
  			def __init__(     self				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					snake_case		:						int								=				0
  					# max greyscale value for #FFFFFF
  					snake_case		:						List[str]								=				int(self.get_greyscale(255				, 255				, 255							)							)
  
  					if not self.min_threshold < threshold < self.max_threshold:
  							snake_case		:						Union[str, Any]								=				F'''Factor value should be from 0 to {self.max_threshold}'''
  							raise ValueError(SCREAMING_SNAKE_CASE							)
  
  					snake_case		:						str								=				input_img
  					snake_case		:						Optional[Any]								=				threshold
  					snake_case			,				snake_case		:						List[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
  					snake_case		:						Union[str, Any]								=				[
  					    [0 for _ in range(self.height + 4							)] for __ in range(self.width + 1							)
  					]
  					snake_case		:						Tuple								=				np.ones((self.width, self.height, 3)				, np.uinta							) * 255
  
  
  			@classmethod
  			def 							lowerCamelCase_				(     cls				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE				, SCREAMING_SNAKE_CASE							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					return 0.1_14 * blue + 0.5_87 * green + 0.21_26 * red
  
  
  
  			def 							lowerCamelCase_				(     self							):
  
  
  
  					"""simple docstring"""
  
  
  
  
  
  
  
  					for y in range(self.height							):
  							for x in range(self.width							):
  									snake_case		:						Dict								=				int(self.get_greyscale(*self.input_img[y][x]							)							)
  									if self.threshold > greyscale + self.error_table[y][x]:
  											snake_case		:						List[str]								=				(0, 0, 0)
  											snake_case		:						List[Any]								=				greyscale + self.error_table[x][y]
  									else:
  											snake_case		:						int								=				(255, 255, 255)
  											snake_case		:						Tuple								=				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
  							__A 		=			[
  							    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()
  
  