



'''simple docstring'''



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



def 	__lowerCAmelCase       (				lowerCamelCase :    List[str]					,		lowerCamelCase :    Optional[Any]       ):






	'''simple docstring'''




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

	return image_array



def 	__lowerCAmelCase       (				lowerCamelCase :    Tuple					,		lowerCamelCase :    Union[str, Any]       ):






	'''simple docstring'''




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

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

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


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



'''simple docstring'''






import os






def 						_A					() ->	int:




     '''simple docstring'''



     _a         =				os.path.dirname(os.path.realpath(lowerCAmelCase__		)		)
     _a         =				os.path.join(lowerCAmelCase__					,    'triangle.txt'		)

     with open(lowerCAmelCase__		) as in_file:
          _a         =				[[int(lowerCAmelCase__		) for i in line.split()] for line in in_file]

     while len(lowerCAmelCase__		) != 1:
          _a         =				triangle.pop()
          _a         =				triangle[-1]
          for j in range(len(lowerCAmelCase__		) - 1		):
               curr_row[j] += max(last_row[j]					,    last_row[j + 1]		)
     return triangle[0][0]


if __name__ == "__main__":
 print(solution())

