





from __future__ import annotations


def 							SCREAMING_SNAKE_CASE__  (      __a				):
	snake_case_						:     Tuple     =		len(__a				)
	# We need to create solution object to save path.
	snake_case_						:     Dict     =		[[0 for _ in range(__a				)] for _ in range(__a				)]
	snake_case_						:     Any     =		run_maze(__a				,	0				,	0				,	__a				)
	if solved:
		print('\n'.join(str(__a				) for row in solutions				)				)
	else:
		print('No solution exists!'				)
	return solved


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				,	__a				,	__a				):
	snake_case_						:     int     =		len(__a				)
	# Final check point.
	if i == j == (size - 1):
		snake_case_						:     Tuple     =		1
		return True

	snake_case_						:     Any     =		(not i < 0) and (not j < 0)  # Check lower bounds
	snake_case_						:     Any     =		(i < size) and (j < size)  # Check upper bounds

	if lower_flag and upper_flag:
		# check for already visited and block points.
		snake_case_						:     Tuple     =		(not solutions[i][j]) and (not maze[i][j])
		if block_flag:
			# check visited
			snake_case_						:     str     =		1

			# check for directions
			if (
			    run_maze(__a				,	i + 1				,	__a				,	__a				)
			    or run_maze(__a				,	__a				,	j + 1				,	__a				)
			    or run_maze(__a				,	i - 1				,	__a				,	__a				)
			    or run_maze(__a				,	__a				,	j - 1				,	__a				)
			):
				return True

			snake_case_						:     Optional[Any]     =		0
			return False
	return False


if __name__ == "__main__":
					import doctest

					doctest.testmod()








from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				):
	snake_case_						:     List[Any]     =		k_size // 2
	snake_case_  ,snake_case_						:     Any     =		mgrid[0 - center : k_size - center, 0 - center : k_size - center]
	snake_case_						:     Optional[Any]     =		1 / (2 * pi * sigma) * exp(-(square(__a				) + square(__a				)) / (2 * square(__a				))				)
	return g


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				,	__a				):
	snake_case_  ,snake_case_						:     Union[str, Any]     =		image.shape[0], image.shape[1]
	# dst image height and width
	snake_case_						:     int     =		height - k_size + 1
	snake_case_						:     Optional[int]     =		width - k_size + 1

	# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
	snake_case_						:     Optional[Any]     =		zeros((dst_height * dst_width, k_size * k_size)				)
	snake_case_						:     Tuple     =		0
	for i, j in product(range(__a				)				,	range(__a				)				):
		snake_case_						:     Optional[int]     =		ravel(image[i : i + k_size, j : j + k_size]				)
		snake_case_						:     str     =		window
		row += 1

	#  turn the kernel into shape(k*k, 1)
	snake_case_						:     List[Any]     =		gen_gaussian_kernel(__a				,	__a				)
	snake_case_						:     str     =		ravel(__a				)

	# reshape and get the dst image
	snake_case_						:     Optional[int]     =		dot(__a				,	__a				).reshape(__a				,	__a				).astype(__a				)

	return dst


if __name__ == "__main__":
						# read original image
						_SCREAMING_SNAKE_CASE 		=						imread(R"""../image_data/lena.jpg""")
						# turn image in gray scale value
						_SCREAMING_SNAKE_CASE 		=						cvtColor(img, COLOR_BGR2GRAY)

						# get values with two different mask size
						_SCREAMING_SNAKE_CASE 		=						gaussian_filter(gray, 3, sigma=1)
						_SCREAMING_SNAKE_CASE 		=						gaussian_filter(gray, 5, sigma=0.8)

						# show result images
						imshow("""gaussian filter with 3x3 mask""", gaussianaxa)
						imshow("""gaussian filter with 5x5 mask""", gaussianaxa)
						waitKey()

