
'''simple docstring'''





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



class 			lowerCAmelCase__ :



  '''simple docstring'''






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

        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 		_lowerCamelCase						(cls	:			Tuple						,			lowerCAmelCase_	:			int						,			lowerCAmelCase_	:			int						,			lowerCAmelCase_	:			int     ) ->							float:
        return 0.114 * blue + 0.587 * green + 0.2_126 * red


  def 		_lowerCamelCase						(self	:			Union[str, Any]     ) ->							None:
        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
     A							     = [
         Burkes(imread("image_data/lena.jpg", 1), threshold)
         for threshold in (1, 1_2_6, 1_3_0, 1_4_0)
     ]

     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()



"""simple docstring"""
import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property




class  _snake_case	(    unittest.TestCase							):






							@cached_property
							def 				__lowercase	(       self    :      str     ):






												"""simple docstring"""



												return BlenderbotTokenizer.from_pretrained("""facebook/blenderbot-3B"""     )






							@cached_property
							def 				__lowercase	(       self    :      str     ):






												"""simple docstring"""



												return BlenderbotTokenizerFast.from_pretrained("""facebook/blenderbot-3B"""     )






							def 				__lowercase	(       self    :      int     ):






												"""simple docstring"""



												__a:    Optional[int]		     =       self.tokenizer_ab
												__a:    Union[str, Any]		     =       """ I am a small frog."""
												__a:    str		     =       tok([src_text]    ,			padding=snake_case__    ,			truncation=snake_case__     )["""input_ids"""]
												__a:    Optional[Any]		     =       tok.batch_decode(snake_case__    ,			skip_special_tokens=snake_case__    ,			clean_up_tokenization_spaces=snake_case__     )[0]
												assert src_text == decoded






							def 				__lowercase	(       self    :      List[Any]     ):






												"""simple docstring"""



												__a:    str		     =       self.rust_tokenizer_ab
												__a:    Optional[Any]		     =       """ I am a small frog."""
												__a:    str		     =       tok([src_text]    ,			padding=snake_case__    ,			truncation=snake_case__     )["""input_ids"""]
												__a:    Union[str, Any]		     =       tok.batch_decode(snake_case__    ,			skip_special_tokens=snake_case__    ,			clean_up_tokenization_spaces=snake_case__     )[0]
												assert src_text == decoded






							def 				__lowercase	(       self    :      List[str]     ):






												"""simple docstring"""



												assert self.tokenizer_ab.add_prefix_space
												assert self.tokenizer_ab([""" Sam""", """Sam"""]     ).input_ids == [[5_5_0_2, 2], [5_5_0_2, 2]]






							def 				__lowercase	(       self    :      Any     ):






												"""simple docstring"""



												assert self.rust_tokenizer_ab.add_prefix_space
												assert self.rust_tokenizer_ab([""" Sam""", """Sam"""]     ).input_ids == [[5_5_0_2, 2], [5_5_0_2, 2]]
