


def 	a__ (							A__,			A__							):







			if n == 0:
						return 1

			elif n % 2 == 1:
						return binary_exponentiation(A__,			n - 1							) * a

			else:
						SCREAMING_SNAKE_CASE_		:    Union[str, Any] 		=				binary_exponentiation(A__,			n / 2							)
						return b * b


if __name__ == "__main__":
			try:
						lowerCAmelCase__ :			Union[str, Any]         =int(input('Enter Base : ').strip())
						lowerCAmelCase__ :			Union[str, Any]         =int(input('Enter Power : ').strip())
			except ValueError:
						print('Invalid literal for integer')

			lowerCAmelCase__ :			Any         =binary_exponentiation(BASE, POWER)
			print(F"""{BASE}^({POWER}) : {RESULT}""")









import cva
import numpy as np






def 	a__ (							A__,			A__,			A__,			A__							):

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






def 	a__ (							A__,			A__,			A__							):
			SCREAMING_SNAKE_CASE_		:    Optional[int] 		=				image[x_coordinate][y_coordinate]
			SCREAMING_SNAKE_CASE_		:    str 		=				[1, 2, 4, 8, 1_6, 3_2, 6_4, 1_2_8]

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

			# Starting from the top right, assigning value to pixels clockwise
			SCREAMING_SNAKE_CASE_		:    Optional[int] 		=				[
			    get_neighbors_pixel(A__,			x_coordinate - 1,			y_coordinate + 1,			A__							),
			    get_neighbors_pixel(A__,			A__,			y_coordinate + 1,			A__							),
			    get_neighbors_pixel(A__,			x_coordinate - 1,			A__,			A__							),
			    get_neighbors_pixel(A__,			x_coordinate + 1,			y_coordinate + 1,			A__							),
			    get_neighbors_pixel(A__,			x_coordinate + 1,			A__,			A__							),
			    get_neighbors_pixel(A__,			x_coordinate + 1,			y_coordinate - 1,			A__							),
			    get_neighbors_pixel(A__,			A__,			y_coordinate - 1,			A__							),
			    get_neighbors_pixel(A__,			x_coordinate - 1,			y_coordinate - 1,			A__							),
			]

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


if __name__ == "__main__":
				# Reading the image and converting it to grayscale.
				lowerCAmelCase__ :			List[Any]         =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__ :			List[Any]         =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__ :			Optional[Any]         =local_binary_value(image, i, j)

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





