




import cva
import numpy as np

def 	lowerCAmelCase_	(     lowerCamelCase:				np.ndarray   , lowerCamelCase:				int   , lowerCamelCase:				int   , lowerCamelCase:				int  )    ->	int:


      '''simple docstring'''




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

def 	lowerCAmelCase_	(     lowerCamelCase:				np.ndarray   , lowerCamelCase:				int   , lowerCamelCase:				int  )    ->	int:


      '''simple docstring'''




      lowerCamelCase__					     = image[x_coordinate][y_coordinate]
      lowerCamelCase__					     = [1, 2, 4, 8, 16, 32, 64, 1_28]

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

      # Starting from the top right, assigning value to pixels clockwise
      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   , 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.
      __SCREAMING_SNAKE_CASE			:      Dict      			=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
      __SCREAMING_SNAKE_CASE			:      str      			=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]):
                  __SCREAMING_SNAKE_CASE			:      List[str]      			=local_binary_value(image, i, j)

      cva.imshow("""local binary pattern""", lbp_image)
      cva.waitKey(0)
      cva.destroyAllWindows()


from typing import Callable




def        lowerCAmelCase(	SCREAMING_SNAKE_CASE_       )->		List[Any]:



    """simple docstring"""






    def wrapper(SCREAMING_SNAKE_CASE_       ):
        UpperCamelCase_          =		function_with_docstring.__doc__
        return target_function

    return wrapper
