
"""simple docstring"""






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



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

			return image_array



def     lowerCAmelCase__ (		__magic_name__ ,      __magic_name__			)	->int:
			__lowercase      ,				__lowercase						      =					image.shape[0], image.shape[1]
			__lowercase						      =					filter_kernel.shape[0]
			__lowercase						      =					k_size // 2
			# Pads image with the edge values of array.
			__lowercase						      =					pad(__magic_name__ ,      __magic_name__ ,      mode="edge"			)

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

			#  turn the kernel into shape(k*k, 1)
			__lowercase						      =					ravel(__magic_name__			)
			# reshape and get the dst image
			__lowercase						      =					dot(__magic_name__ ,      __magic_name__			).reshape(__magic_name__ ,      __magic_name__			)
			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)
					# Laplace operator
					_lowercase							 =							array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
					_lowercase							 =							img_convolve(gray, Laplace_kernel).astype(uinta)
					imshow('''Laplacian''', out)
					waitKey(0)







"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowercase							 =							{'''configuration_sew_d''': ['''SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SEWDConfig''']}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowercase							 =							[
					    '''SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''SEWDForCTC''',
					    '''SEWDForSequenceClassification''',
					    '''SEWDModel''',
					    '''SEWDPreTrainedModel''',
					]

if TYPE_CHECKING:
					from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_sew_d import (
										    SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SEWDForCTC,
										    SEWDForSequenceClassification,
										    SEWDModel,
										    SEWDPreTrainedModel,
										)


else:
					import sys

					_lowercase							 =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





