

'''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__    (      UpperCAmelCase__,       UpperCAmelCase__				)			->			Optional[int]:
       A_						=      k_size // 2
       A_					,			A_						=      mgrid[0 - center : k_size - center, 0 - center : k_size - center]
       A_						=      1 / (2 * pi * sigma) * exp(-(square(__snake_case				) + square(__snake_case				)) / (2 * square(__snake_case				))				)
       return g
def       UpperCAmelCase__    (      UpperCAmelCase__,       UpperCAmelCase__,       UpperCAmelCase__				)			->			Union[str, Any]:
       A_					,			A_						=      image.shape[0], image.shape[1]
       # dst image height and width
       A_						=      height - k_size + 1
       A_						=      width - k_size + 1

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

       #  turn the kernel into shape(k*k, 1)
       A_						=      gen_gaussian_kernel(__snake_case,       __snake_case				)
       A_						=      ravel(__snake_case				)

       # reshape and get the dst image
       A_						=      dot(__snake_case,       __snake_case				).reshape(__snake_case,       __snake_case				).astype(__snake_case				)

       return dst


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

      # get values with two different mask size
      __lowerCamelCase		       =    gaussian_filter(gray, 3, sigma=1)
      __lowerCamelCase		       =    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'''







def       UpperCAmelCase__    (      UpperCAmelCase__,       UpperCAmelCase__,       UpperCAmelCase__ = 0,       UpperCAmelCase__ = 0				)			->			int:
       A_						=      right or len(UpperCAmelCase__				) - 1
       if left > right:
              return -1
       elif list_data[left] == key:
              return left
       elif list_data[right] == key:
              return right
       else:
              return search(UpperCAmelCase__,       UpperCAmelCase__,       left + 1,       right - 1				)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
