





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





def    _lowercase    (  _UpperCAmelCase	,					_UpperCAmelCase )  ->     str:
				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	,					_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    _lowercase    (  _UpperCAmelCase	,					_UpperCAmelCase )  ->     Union[str, Any]:
				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(_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
							UpperCAmelCase__  :	Any     =imread(r'''../image_data/lena.jpg''')
							# turn image in gray scale value
							UpperCAmelCase__  :	Any     =cvtColor(img, COLOR_BGR2GRAY)
							# Laplace operator
							UpperCAmelCase__  :	List[Any]     =array([[0, 1, 0], [1, -4, 1], [0, 1, 0]])
							UpperCAmelCase__  :	Dict     =img_convolve(gray, Laplace_kernel).astype(uinta)
							imshow('''Laplacian''', out)
							waitKey(0)












from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase__  :	Optional[Any]     ={'''configuration_pegasus''': ['''PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusConfig''']}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__  :	Union[str, Any]     =['''PegasusTokenizer''']

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__  :	int     =['''PegasusTokenizerFast''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__  :	str     =[
							    '''PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''PegasusForCausalLM''',
							    '''PegasusForConditionalGeneration''',
							    '''PegasusModel''',
							    '''PegasusPreTrainedModel''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__  :	Union[str, Any]     =[
							    '''TFPegasusForConditionalGeneration''',
							    '''TFPegasusModel''',
							    '''TFPegasusPreTrainedModel''',
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__  :	Dict     =[
							    '''FlaxPegasusForConditionalGeneration''',
							    '''FlaxPegasusModel''',
							    '''FlaxPegasusPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_pegasus import PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_pegasus import PegasusTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_pegasus_fast import PegasusTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_pegasus import (
														    PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
														    PegasusForCausalLM,
														    PegasusForConditionalGeneration,
														    PegasusModel,
														    PegasusPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_pegasus import TFPegasusForConditionalGeneration, TFPegasusModel, TFPegasusPreTrainedModel

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_pegasus import (
														    FlaxPegasusForConditionalGeneration,
														    FlaxPegasusModel,
														    FlaxPegasusPreTrainedModel,
														)

else:
							import sys

							UpperCAmelCase__  :	Union[str, Any]     =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





