






import math
import sys

import cva
import numpy as np







def 			__lowercase							(      _a  :					np.ndarray		,  _a  :					float	):





 '''simple docstring'''







 snake_case__  :    Optional[Any]							       =math.sqrt(_a	)
 snake_case__  :    Dict							       =1 / (sigma * math.sqrt(2 * math.pi	))
 return cons * np.exp(-((img / sigma) ** 2) * 0.5	)







def 			__lowercase							(      _a  :					np.ndarray		,  _a  :					int		,  _a  :					int		,  _a  :					int	):





 '''simple docstring'''







 snake_case__  :    Union[str, Any]							       =kernel_size // 2
 return img[x - half : x + half + 1, y - half : y + half + 1]







def 			__lowercase							(      _a  :					int		,  _a  :					float	):





 '''simple docstring'''







 snake_case__  :    Union[str, Any]							       =np.zeros((kernel_size, kernel_size)	)
 for i in range(0		,  _a	):
  for j in range(0		,  _a	):
   snake_case__  :    Any							       =math.sqrt(
       abs(i - kernel_size // 2	) ** 2 + abs(j - kernel_size // 2	) ** 2	)
 return vec_gaussian(_a		,  _a	)







def 			__lowercase							(      _a  :					np.ndarray		,  _a  :					float		,  _a  :					float		,  _a  :					int		,  ):





 '''simple docstring'''







 snake_case__  :    str							       =np.zeros(img.shape	)
 snake_case__  :    List[Any]							       =get_gauss_kernel(_a		,  _a	)
 snake_case__  :    Union[str, Any]							       =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__  :    Any							       =get_slice(_a		,  _a		,  _a		,  _a	)
   snake_case__  :    List[str]							       =img_s - img_s[kernel_size // 2, kernel_size // 2]
   snake_case__  :    List[str]							       =vec_gaussian(_a		,  _a	)
   snake_case__  :    str							       =np.multiply(_a		,  _a	)
   snake_case__  :    Optional[int]							       =np.multiply(_a		,  _a	)
   snake_case__  :    Dict							       =np.sum(_a	) / np.sum(_a	)
   snake_case__  :    Tuple							       =val
 return imga







def 			__lowercase							(      _a  :					list	):





 '''simple docstring'''







 snake_case__  :    str							       =args[1] if args[1:] else """../image_data/lena.jpg"""
 snake_case__  :    Optional[Any]							       =float(args[2]	) if args[2:] else 1.0
 snake_case__  :    Tuple							       =float(args[3]	) if args[3:] else 1.0
 if args[4:]:
  snake_case__  :    Union[str, Any]							       =int(args[4]	)
  snake_case__  :    Optional[int]							       =kernel_size + abs(kernel_size % 2 - 1	)
 else:
  snake_case__  :    List[str]							       =5
 return filename, spatial_variance, intensity_variance, kernel_size


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

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













def 			A__							(      _a  :					Any		,  _a  :					Optional[Any]		,  _a  :					int		,  _a  :					Any	):





 '''simple docstring'''







 if height >= 1:
  move_tower(height - 1		,  _a		,  _a		,  _a	)
  move_disk(_a		,  _a	)
  move_tower(height - 1		,  _a		,  _a		,  _a	)







def 			A__							(      _a  :					Optional[int]		,  _a  :					str	):





 '''simple docstring'''







 print("""moving disk from"""		,  _a		,  """to"""		,  _a	)







def 			A__							(      ):





 '''simple docstring'''







 snake_case__  :    Dict							       =int(input("""Height of hanoi: """	).strip()	)
 move_tower(_a		,  """A"""		,  """B"""		,  """C"""	)


if __name__ == "__main__":
       main()





