





import cva
import numpy as np







def      A__				(       SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__)  ->       int:

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







def      A__				(       SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__)  ->       int:
  __snake_case:		str					    =		image[x_coordinate][y_coordinate]
  __snake_case:		Union[str, Any]					    =		[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
  __snake_case:		Any					    =		[
      get_neighbors_pixel(SCREAMING_SNAKE_CASE__   ,   x_coordinate - 1   ,   y_coordinate + 1   ,   SCREAMING_SNAKE_CASE__),
      get_neighbors_pixel(SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__   ,   y_coordinate + 1   ,   SCREAMING_SNAKE_CASE__),
      get_neighbors_pixel(SCREAMING_SNAKE_CASE__   ,   x_coordinate - 1   ,   SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__),
      get_neighbors_pixel(SCREAMING_SNAKE_CASE__   ,   x_coordinate + 1   ,   y_coordinate + 1   ,   SCREAMING_SNAKE_CASE__),
      get_neighbors_pixel(SCREAMING_SNAKE_CASE__   ,   x_coordinate + 1   ,   SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__),
      get_neighbors_pixel(SCREAMING_SNAKE_CASE__   ,   x_coordinate + 1   ,   y_coordinate - 1   ,   SCREAMING_SNAKE_CASE__),
      get_neighbors_pixel(SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__   ,   y_coordinate - 1   ,   SCREAMING_SNAKE_CASE__),
      get_neighbors_pixel(SCREAMING_SNAKE_CASE__   ,   x_coordinate - 1   ,   y_coordinate - 1   ,   SCREAMING_SNAKE_CASE__),
  ]

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


if __name__ == "__main__":
      # Reading the image and converting it to grayscale.
      __UpperCAmelCase			:  Optional[int]										=				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
      __UpperCAmelCase			:  Dict										=				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]):
                  __UpperCAmelCase			:  List[str]										=				local_binary_value(image, i, j)

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













from functools import lru_cache







@lru_cache
def      A__				(       SCREAMING_SNAKE_CASE__)  ->       int:
  if not isinstance(SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__):
    raise TypeError("""k must be an integer.""")
  if k < 0:
    raise ValueError("""k integer must be greater or equal to zero.""")
  if k == 0:
    return 0
  elif k == 1:
    return 1
  else:
    return fibonacci(k - 1) + fibonacci(k - 2)







def      A__				(       SCREAMING_SNAKE_CASE__   ,   SCREAMING_SNAKE_CASE__)  ->       int:
  __snake_case:		str					    =		len(SCREAMING_SNAKE_CASE__)
  # Find m such that F_m >= n where F_i is the i_th fibonacci number.
  __snake_case:		Optional[int]					    =		0
  while True:
    if fibonacci(SCREAMING_SNAKE_CASE__) >= len_list:
      __snake_case:		str					    =		i
      break
    i += 1
  __snake_case:		Tuple					    =		0
  while fibb_k > 0:
    __snake_case:		str					    =		min(
        offset + fibonacci(fibb_k - 1)   ,   len_list - 1)  # Prevent out of range
    __snake_case:		List[Any]					    =		arr[index_k]
    if item_k_1 == val:
      return index_k
    elif val < item_k_1:
      fibb_k -= 1
    elif val > item_k_1:
      offset += fibonacci(fibb_k - 1)
      fibb_k -= 2
  else:
    return -1


if __name__ == "__main__":
      import doctest

      doctest.testmod()






