



from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import array, dot, pad, ravel, uinta, zeros

def      A_ (		__a       :			str	,						__a       :			List[str]						):

				"""simple docstring"""
				a__ ,     a__			 =						image.shape
				a__			 =						cols - block_size[1] + 1
				a__			 =						rows - block_size[0] + 1
				a__			 =						zeros((dst_height * dst_width, block_size[1] * block_size[0])						)
				a__			 =						0
				for i in range(0	,						__a						):
								for j in range(0	,						__a						):
												a__			 =						ravel(image[i : i + block_size[0], j : j + block_size[1]]						)
												a__			 =						window
												row += 1

				return image_array

def      A_ (		__a       :			Optional[int]	,						__a       :			int						):

				"""simple docstring"""
				a__ ,     a__			 =						image.shape[0], image.shape[1]
				a__			 =						filter_kernel.shape[0]
				a__			 =						k_size // 2
				# Pads image with the edge values of array.
				a__			 =						pad(__a	,						__a	,						mode="""edge"""						)

				# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
				a__			 =						imacol(__a	,						(k_size, k_size)						)

				#  turn the kernel into shape(k*k, 1)
				a__			 =						ravel(__a						)
				# reshape and get the dst image
				a__			 =						dot(__a	,						__a						).reshape(__a	,						__a						)
				return dst


if __name__ == "__main__":
	# read original image
	UpperCAmelCase								=   imread(R"""../image_data/lena.jpg""")
	# turn image in gray scale value
	UpperCAmelCase								=   cvtColor(img, COLOR_BGR2GRAY)
	# Laplace operator
	UpperCAmelCase								=   array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
	UpperCAmelCase								=   img_convolve(gray, Laplace_kernel).astype(uinta)
	imshow("""Laplacian""", out)
	waitKey(0)






def      A_ (		__a       :			float						):

				"""simple docstring"""
				return int(__a						) if x - int(__a						) >= 0 else int(__a						) - 1


if __name__ == "__main__":
	import doctest

	doctest.testmod()

