





'''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 	__a(SCREAMING_SNAKE_CASE_  :					List[str]		,       SCREAMING_SNAKE_CASE_  :					int    ):



    '''simple docstring'''





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


def 	__a(SCREAMING_SNAKE_CASE_  :					Optional[Any]		,       SCREAMING_SNAKE_CASE_  :					Union[str, Any]		,       SCREAMING_SNAKE_CASE_  :					List[str]    ):



    '''simple docstring'''





    _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(__lowerCAmelCase    )		,       range(__lowerCAmelCase    )    ):
        _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(__lowerCAmelCase		,       __lowerCAmelCase    )
    _lowerCAmelCase				=      ravel(__lowerCAmelCase    )

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

    return dst


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

       # get values with two different mask size
       _SCREAMING_SNAKE_CASE	 =							gaussian_filter(gray, 3, sigma=1)
       _SCREAMING_SNAKE_CASE	 =							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 __future__ import annotations


def 	__a(SCREAMING_SNAKE_CASE_  :					list[float]		,       SCREAMING_SNAKE_CASE_  :					list[float]    ):



    '''simple docstring'''





    _lowerCAmelCase				=      sorted(numsa + numsa    )
    _lowerCAmelCase			,			_lowerCAmelCase				=      divmod(len(SCREAMING_SNAKE_CASE_    )		,       2    )
    if mod == 1:
        return all_numbers[div]
    else:
        return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       _SCREAMING_SNAKE_CASE	 =							[float(x) for x in input("Enter the elements of first array: ").split()]
       _SCREAMING_SNAKE_CASE	 =							[float(x) for x in input("Enter the elements of second array: ").split()]
       print(f'''The median of two arrays is: {median_of_two_arrays(array_a, array_a)}''')


