





'''simple docstring'''






from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def   UpperCamelCase__ (						lowerCAmelCase				,      lowerCAmelCase    ):





      """simple docstring"""


      _lowerCAmelCase					=				k_size // 2
      _lowerCAmelCase	,				_lowerCAmelCase					=				mgrid[0 - center : k_size - center, 0 - center : k_size - center]
      _lowerCAmelCase					=				1 / (2 * pi * sigma) * exp(-(square(__a    ) + square(__a    )) / (2 * square(__a    ))    )
      return g
def   UpperCamelCase__ (						lowerCAmelCase				,      lowerCAmelCase				,      lowerCAmelCase    ):





      """simple docstring"""


      _lowerCAmelCase	,				_lowerCAmelCase					=				image.shape[0], image.shape[1]
      # dst image height and width
      _lowerCAmelCase					=				height - k_size + 1
      _lowerCAmelCase					=				width - k_size + 1

      # im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
      _lowerCAmelCase					=				zeros((dst_height * dst_width, k_size * k_size)    )
      _lowerCAmelCase					=				0
      for i, j in product(range(__a    )				,      range(__a    )    ):
            _lowerCAmelCase					=				ravel(image[i : i + k_size, j : j + k_size]    )
            _lowerCAmelCase					=				window
            row += 1

      #  turn the kernel into shape(k*k, 1)
      _lowerCAmelCase					=				gen_gaussian_kernel(__a				,      __a    )
      _lowerCAmelCase					=				ravel(__a    )

      # reshape and get the dst image
      _lowerCAmelCase					=				dot(__a				,      __a    ).reshape(__a				,      __a    ).astype(__a    )

      return dst


if __name__ == "__main__":
      # read original image
      A__							:  Tuple    =imread(r'''../image_data/lena.jpg''')
      # turn image in gray scale value
      A__							:  List[str]    =cvtColor(img, COLOR_BGR2GRAY)

      # get values with two different mask size
      A__							:  str    =gaussian_filter(gray, 3, sigma=1)
      A__							:  str    =gaussian_filter(gray, 5, sigma=0.8)

      # show result images
      imshow('''gaussian filter with 3x3 mask''', gaussianaxa)
      imshow('''gaussian filter with 5x5 mask''', gaussianaxa)
      waitKey()








"""simple docstring"""





from typing import TYPE_CHECKING

from ..utils import _LazyModule


UpperCamelCase_       :    Dict						      =			{
    '''config''': [
        '''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
        '''OnnxConfig''',
        '''OnnxConfigWithPast''',
        '''OnnxSeq2SeqConfigWithPast''',
        '''PatchingSpec''',
    ],
    '''convert''': ['''export''', '''validate_model_outputs'''],
    '''features''': ['''FeaturesManager'''],
    '''utils''': ['''ParameterFormat''', '''compute_serialized_parameters_size'''],
}


if TYPE_CHECKING:
		from .config import (
		    EXTERNAL_DATA_FORMAT_SIZE_LIMIT,
		    OnnxConfig,
		    OnnxConfigWithPast,
		    OnnxSeqaSeqConfigWithPast,
		    PatchingSpec,
		)
		from .convert import export, validate_model_outputs
		from .features import FeaturesManager
		from .utils import ParameterFormat, compute_serialized_parameters_size

else:
		import sys

		UpperCamelCase_       :    List[Any]						      =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




