


"""simple docstring"""



from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import array, dot, pad, ravel, uinta, zeros
def     UpperCAmelCase    (					_lowercase   :      List[str] ,      _lowercase   :      Optional[Any]  )	->   Optional[Any]:


	"""simple docstring"""




	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 ,      UpperCamelCase__  ):
		for j in range(0 ,      UpperCamelCase__  ):
			lowerCAmelCase_       = ravel(image[i : i + block_size[0], j : j + block_size[1]]  )
			lowerCAmelCase_       = window
			row += 1

	return image_array
def     UpperCAmelCase    (					_lowercase   :      str ,      _lowercase   :      List[Any]  )	->   int:


	"""simple docstring"""




	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(UpperCamelCase__ ,      UpperCamelCase__ ,      mode='''edge'''  )

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

	#  turn the kernel into shape(k*k, 1)
	lowerCAmelCase_       = ravel(UpperCamelCase__  )
	# reshape and get the dst image
	lowerCAmelCase_       = dot(UpperCamelCase__ ,      UpperCamelCase__  ).reshape(UpperCamelCase__ ,      UpperCamelCase__  )
	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_prophetnet': ['PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ProphetNetConfig'],
    'tokenization_prophetnet': ['ProphetNetTokenizer'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase_							 =       [
		    'PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ProphetNetDecoder',
		    'ProphetNetEncoder',
		    'ProphetNetForCausalLM',
		    'ProphetNetForConditionalGeneration',
		    'ProphetNetModel',
		    'ProphetNetPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_prophetnet import PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ProphetNetConfig
		from .tokenization_prophetnet import ProphetNetTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_prophetnet import (
				    PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ProphetNetDecoder,
				    ProphetNetEncoder,
				    ProphetNetForCausalLM,
				    ProphetNetForConditionalGeneration,
				    ProphetNetModel,
				    ProphetNetPreTrainedModel,
				)

else:
		import sys

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