




import cva
import numpy as np



def     lowerCAmelCase		(		_lowerCAmelCase				: np.ndarray    ,				_lowerCAmelCase				: int    ,				_lowerCAmelCase				: int    ,				_lowerCAmelCase				: 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						):




 """simple docstring"""







 UpperCAmelCase__							=    image[x_coordinate][y_coordinate]
 UpperCAmelCase__							=    [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__							=    [
     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.
  _lowerCAmelCase    : str		= 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
  _lowerCAmelCase    : 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]):
      _lowerCAmelCase    : List[Any]		= local_binary_value(image, i, j)

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











def     lowerCAmelCase		(		_lowerCAmelCase				: Tuple    ,				_lowerCAmelCase				: Tuple						):




 """simple docstring"""







 sequence.append(_lowerCAmelCase						)

 UpperCAmelCase__							=    0
 while sequence[index] != target:
  index += 1

 sequence.pop()

 if index == len(_lowerCAmelCase						):
  return None

 return index


if __name__ == "__main__":
  _lowerCAmelCase    : List[Any]		= input("Enter numbers separated by comma:\n").strip()
  _lowerCAmelCase    : Dict		= [int(item) for item in user_input.split(",")]

  _lowerCAmelCase    : Optional[Any]		= input("Enter a single number to be found in the list:\n")
  _lowerCAmelCase    : Tuple		= int(target_input)
  _lowerCAmelCase    : int		= sentinel_linear_search(sequence, target)
  if result is not None:
    print(F'''{target} found at positions: {result}''')
  else:
    print("Not found")





