

'''simple docstring'''

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

def 			__UpperCamelCase							(		lowercase__  :					Optional[Any],   lowercase__  :					Optional[int]	):






     '''simple docstring'''





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

     return image_array

def 			__UpperCamelCase							(		lowercase__  :					List[str],   lowercase__  :					Optional[int]	):






     '''simple docstring'''





     __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(lowercase__,   lowercase__,   mode='edge'	)

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

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





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase							=					{'''configuration_vit_hybrid''': ['''VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTHybridConfig''']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase							=					[
           '''VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''ViTHybridForImageClassification''',
           '''ViTHybridModel''',
           '''ViTHybridPreTrainedModel''',
       ]

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase							=					['''ViTHybridImageProcessor''']


if TYPE_CHECKING:
       from .configuration_vit_hybrid import VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTHybridConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_vit_hybrid import (
                  VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ViTHybridForImageClassification,
                  ViTHybridModel,
                  ViTHybridPreTrainedModel,
              )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_vit_hybrid import ViTHybridImageProcessor


else:
       import sys

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


