'''simple docstring'''




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 				snake_case__							(			_A:					int      ,   _A:					Tuple )    ->	Dict:

		'''simple docstring'''


		lowerCAmelCase   					=  k_size // 2
		lowerCAmelCase					,     lowerCAmelCase   					=  mgrid[0 - center : k_size - center, 0 - center : k_size - center]
		lowerCAmelCase   					=  1 / (2 * pi * sigma) * exp(-(square(_A ) + square(_A )) / (2 * square(_A )) )
		return g






def 				snake_case__							(			_A:					List[str]      ,   _A:					Tuple      ,   _A:					Optional[Any] )    ->	Dict:

		'''simple docstring'''


		lowerCAmelCase					,     lowerCAmelCase   					=  image.shape[0], image.shape[1]
		# dst image height and width
		lowerCAmelCase   					=  height - k_size + 1
		lowerCAmelCase   					=  width - k_size + 1

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

		#  turn the kernel into shape(k*k, 1)
		lowerCAmelCase   					=  gen_gaussian_kernel(_A      ,   _A )
		lowerCAmelCase   					=  ravel(_A )

		# reshape and get the dst image
		lowerCAmelCase   					=  dot(_A      ,   _A ).reshape(_A      ,   _A ).astype(_A )

		return dst


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

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





'''simple docstring'''




from math import sqrt






def 				snake_case__							(			_A:					int = 1000000 )    ->	int:

		'''simple docstring'''


		lowerCAmelCase   					=  0
		lowerCAmelCase   					=  0
		lowerCAmelCase   					=  42

		while num_cuboids <= limit:
				max_cuboid_size += 1
				for sum_shortest_sides in range(2      ,   2 * max_cuboid_size + 1 ):
						if sqrt(sum_shortest_sides**2 + max_cuboid_size**2 ).is_integer():
								num_cuboids += (
								    min(_A      ,   sum_shortest_sides // 2 )
								    - max(1      ,   sum_shortest_sides - max_cuboid_size )
								    + 1
								)

		return max_cuboid_size


if __name__ == "__main__":
						print(f'{solution() = }')




