


import math
import sys

import cva
import numpy as np
def       UpperCAmelCase__						(UpperCamelCase_							,UpperCamelCase_    ):



     """simple docstring"""






     snake_case					=    math.sqrt(UpperCamelCase_    )
     snake_case					=    1 / (sigma * math.sqrt(2 * math.pi    ))
     return cons * np.exp(-((img / sigma) ** 2) * 0.5    )
def       UpperCAmelCase__						(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_    ):



     """simple docstring"""






     snake_case					=    kernel_size // 2
     return img[x - half : x + half + 1, y - half : y + half + 1]
def       UpperCAmelCase__						(UpperCamelCase_							,UpperCamelCase_    ):



     """simple docstring"""






     snake_case					=    np.zeros((kernel_size, kernel_size)    )
     for i in range(0							,UpperCamelCase_    ):
          for j in range(0							,UpperCamelCase_    ):
               snake_case					=    math.sqrt(
                   abs(i - kernel_size // 2    ) ** 2 + abs(j - kernel_size // 2    ) ** 2    )
     return vec_gaussian(UpperCamelCase_							,UpperCamelCase_    )
def       UpperCAmelCase__						(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_							,):



     """simple docstring"""






     snake_case					=    np.zeros(img.shape    )
     snake_case					=    get_gauss_kernel(UpperCamelCase_							,UpperCamelCase_    )
     snake_case			,  snake_case					=    img.shape
     for i in range(kernel_size // 2							,size_x - kernel_size // 2    ):
          for j in range(kernel_size // 2							,size_y - kernel_size // 2    ):
               snake_case					=    get_slice(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_    )
               snake_case					=    img_s - img_s[kernel_size // 2, kernel_size // 2]
               snake_case					=    vec_gaussian(UpperCamelCase_							,UpperCamelCase_    )
               snake_case					=    np.multiply(UpperCamelCase_							,UpperCamelCase_    )
               snake_case					=    np.multiply(UpperCamelCase_							,UpperCamelCase_    )
               snake_case					=    np.sum(UpperCamelCase_    ) / np.sum(UpperCamelCase_    )
               snake_case					=    val
     return imga
def       UpperCAmelCase__						(UpperCamelCase_    ):



     """simple docstring"""






     snake_case					=    args[1] if args[1:] else '''../image_data/lena.jpg'''
     snake_case					=    float(args[2]    ) if args[2:] else 1.0
     snake_case					=    float(args[3]    ) if args[3:] else 1.0
     if args[4:]:
          snake_case					=    int(args[4]    )
          snake_case					=    kernel_size + abs(kernel_size % 2 - 1    )
     else:
          snake_case					=    5
     return filename, spatial_variance, intensity_variance, kernel_size


if __name__ == "__main__":
 _SCREAMING_SNAKE_CASE      :			Optional[Any]      				=   parse_args(sys.argv)
 _SCREAMING_SNAKE_CASE      :			Tuple      				=   cva.imread(filename, 0)
 cva.imshow("input image", img)

 _SCREAMING_SNAKE_CASE      :			Optional[int]      				=   img / 2_55
 _SCREAMING_SNAKE_CASE      :			Optional[Any]      				=   out.astype("float32")
 _SCREAMING_SNAKE_CASE      :			List[Any]      				=   bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
 _SCREAMING_SNAKE_CASE      :			int      				=   out * 2_55
 _SCREAMING_SNAKE_CASE      :			Optional[int]      				=   np.uinta(out)
 cva.imshow("output image", out)
 cva.waitKey(0)
 cva.destroyAllWindows()








def       UpperCAmelCase__						(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_    ):



     """simple docstring"""






     snake_case					=    len(UpperCamelCase_    )
     snake_case					=    [[0] * n for i in range(UpperCamelCase_    )]
     for i in range(UpperCamelCase_    ):
          snake_case					=    y_points[i]

     for i in range(2							,UpperCamelCase_    ):
          for j in range(UpperCamelCase_							,UpperCamelCase_    ):
               snake_case					=    (
                   (xa - x_points[j - i + 1]) * q[j][i - 1]
                   - (xa - x_points[j]) * q[j - 1][i - 1]
               ) / (x_points[j] - x_points[j - i + 1])

     return [q[n - 1][n - 1], q]


if __name__ == "__main__":
 import doctest

 doctest.testmod()




