



'''simple docstring'''
import os
from string import ascii_letters

_UpperCamelCase											=			ascii_letters + ''' \t\n'''


def   lowercase_	(   ):

			"""simple docstring"""





			__UpperCAmelCase   :      int										=     os.path.split(os.path.realpath(lowerCAmelCase__ ) )
			__UpperCAmelCase   :      dict[str, None]										=     {}
			with open(path[0] + """/dictionary.txt""" ) as dictionary_file:
						for word in dictionary_file.read().split("""\n""" ):
									__UpperCAmelCase   :      List[Any]										=     None
			return english_words


_UpperCamelCase											=			load_dictionary()


def   lowercase_	(   lowerCAmelCase__	:  str ):

			"""simple docstring"""





			__UpperCAmelCase   :      Union[str, Any]										=     message.upper()
			__UpperCAmelCase   :      Dict										=     remove_non_letters(lowerCAmelCase__ )
			__UpperCAmelCase   :      Dict										=     message.split()
			__UpperCAmelCase   :      Optional[Any]										=     len([word for word in possible_words if word in ENGLISH_WORDS] )
			return float(lowerCAmelCase__ ) / len(lowerCAmelCase__ )


def   lowercase_	(   lowerCAmelCase__	:  str ):

			"""simple docstring"""





			return "".join(symbol for symbol in message if symbol in LETTERS_AND_SPACE )


def   lowercase_	(   lowerCAmelCase__	:  str			,							lowerCAmelCase__	:  int = 20			,							lowerCAmelCase__	:  int = 85 ):

			"""simple docstring"""





			__UpperCAmelCase   :      Union[str, Any]										=     get_english_count(lowerCAmelCase__ ) * 100 >= word_percentage
			__UpperCAmelCase   :      Tuple										=     len(remove_non_letters(lowerCAmelCase__ ) )
			__UpperCAmelCase   :      List[Any]										=     (float(lowerCAmelCase__ ) / len(lowerCAmelCase__ )) * 100
			__UpperCAmelCase   :      List[Any]										=     message_letters_percentage >= letter_percentage
			return words_match and letters_match


if __name__ == "__main__":
					import doctest

					doctest.testmod()









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



class _A  :





		def __init__(     self ,       __UpperCAmelCase ,       __UpperCAmelCase				)       ->     Union[str, Any]:

					'''simple docstring'''
					__UpperCAmelCase   :      Optional[int]										=     0
					# max greyscale value for #FFFFFF
					__UpperCAmelCase   :      List[Any]										=     int(self.get_greyscale(255 ,       255 ,       255				)				)

					if not self.min_threshold < threshold < self.max_threshold:
								__UpperCAmelCase   :      str										=     f'Factor value should be from 0 to {self.max_threshold}'
								raise ValueError(__UpperCAmelCase				)

					__UpperCAmelCase   :      Tuple										=     input_img
					__UpperCAmelCase   :      Optional[Any]										=     threshold
					__UpperCAmelCase				,  __UpperCAmelCase   :      List[Any]										=     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
					__UpperCAmelCase   :      Optional[Any]										=     [
					    [0 for _ in range(self.height + 4				)] for __ in range(self.width + 1				)
					]
					__UpperCAmelCase   :      Any										=     np.ones((self.width, self.height, 3) ,       np.uinta				) * 255





		@classmethod
		def 							__A       (     cls ,       __UpperCAmelCase ,       __UpperCAmelCase ,       __UpperCAmelCase				)       ->     float:

					'''simple docstring'''
					return 0.114 * blue + 0.587 * green + 0.2126 * red





		def 							__A       (     self				)       ->     None:

					'''simple docstring'''
					for y in range(self.height				):
								for x in range(self.width				):
											__UpperCAmelCase   :      Optional[Any]										=     int(self.get_greyscale(*self.input_img[y][x]				)				)
											if self.threshold > greyscale + self.error_table[y][x]:
														__UpperCAmelCase   :      List[Any]										=     (0, 0, 0)
														__UpperCAmelCase   :      Union[str, Any]										=     greyscale + self.error_table[x][y]
											else:
														__UpperCAmelCase   :      Optional[Any]										=     (255, 255, 255)
														__UpperCAmelCase   :      Dict										=     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
					_UpperCamelCase											=			[
					    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()




