
"""simple docstring"""





import cva
import numpy as np







def       __a	(						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase    ):

   try:
      return int(image[x_coordinate][y_coordinate] >= center    )
   except (IndexError, TypeError):
      return 0







def       __a	(						__lowerCamelCase,						__lowerCamelCase,						__lowerCamelCase    ):
   UpperCAmelCase_   :   Optional[int]     	=       image[x_coordinate][y_coordinate]
   UpperCAmelCase_   :   int     	=       [1, 2, 4, 8, 16, 32, 64, 128]

   # skip get_neighbors_pixel if center is null
   if center is None:
      return 0

   # Starting from the top right, assigning value to pixels clockwise
   UpperCAmelCase_   :   List[Any]     	=       [
       get_neighbors_pixel(__lowerCamelCase,						x_coordinate - 1,						y_coordinate + 1,						__lowerCamelCase    ),
       get_neighbors_pixel(__lowerCamelCase,						__lowerCamelCase,						y_coordinate + 1,						__lowerCamelCase    ),
       get_neighbors_pixel(__lowerCamelCase,						x_coordinate - 1,						__lowerCamelCase,						__lowerCamelCase    ),
       get_neighbors_pixel(__lowerCamelCase,						x_coordinate + 1,						y_coordinate + 1,						__lowerCamelCase    ),
       get_neighbors_pixel(__lowerCamelCase,						x_coordinate + 1,						__lowerCamelCase,						__lowerCamelCase    ),
       get_neighbors_pixel(__lowerCamelCase,						x_coordinate + 1,						y_coordinate - 1,						__lowerCamelCase    ),
       get_neighbors_pixel(__lowerCamelCase,						__lowerCamelCase,						y_coordinate - 1,						__lowerCamelCase    ),
       get_neighbors_pixel(__lowerCamelCase,						x_coordinate - 1,						y_coordinate - 1,						__lowerCamelCase    ),
   ]

   # Converting the binary value to decimal.
   return sum(
       binary_value * power for binary_value, power in zip(__lowerCamelCase,						__lowerCamelCase    )    )


if __name__ == "__main__":
    # Reading the image and converting it to grayscale.
    _a									=				cva.imread(
        'digital_image_processing/image_data/lena.jpg', cva.IMREAD_GRAYSCALE
    )

    # Create a numpy array as the same height and width of read image
    _a									=				np.zeros((image.shape[0], image.shape[1]))

    # Iterating through the image and calculating the
    # local binary pattern value for each pixel.
    for i in range(0, image.shape[0]):
        for j in range(0, image.shape[1]):
            _a									=				local_binary_value(image, i, j)

    cva.imshow('local binary pattern', lbp_image)
    cva.waitKey(0)
    cva.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]]
