


def 			_a      (    __UpperCamelCase			):


     if not isinstance(UpperCamelCase_	,	UpperCamelCase_			):
          a_     :  Any				      =     (
              """operation can not be conducted on a object of type """
              F'''{type(UpperCamelCase_			).__name__}'''
          )
          raise TypeError(UpperCamelCase_			)
     a_     :  Dict				      =     """"""
     for _ in range(0	,	3_2			):
          bit_string += str(number % 2			)
          a_     :  Tuple				      =     number >> 1
     return bit_string



def 			_a      (    __UpperCamelCase			):


     if number < 0:
          raise ValueError("""the value of input must be positive"""			)
     elif isinstance(UpperCamelCase_	,	UpperCamelCase_			):
          raise TypeError("""Input value must be a 'int' type"""			)
     elif isinstance(UpperCamelCase_	,	UpperCamelCase_			):
          raise TypeError("""'<' not supported between instances of 'str' and 'int'"""			)
     a_     :  Dict				      =     0
     # iterator over [1 to 32],since we are dealing with 32 bit integer
     for _ in range(1	,	3_3			):
          # left shift the bits by unity
          a_     :  int				      =     result << 1
          # get the end bit
          a_     :  int				      =     number % 2
          # right shift the bits by unity
          a_     :  str				      =     number >> 1
          # add that bit to our ans
          a_     :  str				      =     result | end_bit
     return get_reverse_bit_string(UpperCamelCase_			)


if __name__ == "__main__":
       import doctest

       doctest.testmod()






"""simple docstring"""





import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey

from digital_image_processing.filters.convolve import img_convolve




def     _A    (    UpperCamelCase_	:			int)      ->		str:
   '''simple docstring'''


   __lowercase								=		np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]])
   __lowercase								=		np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]])

   __lowercase								=		np.abs(img_convolve(UpperCamelCase_,     UpperCamelCase_))
   __lowercase								=		np.abs(img_convolve(UpperCamelCase_,     UpperCamelCase_))
   # modify the pix within [0, 255]
   __lowercase								=		dst_x * 255 / np.max(UpperCamelCase_)
   __lowercase								=		dst_y * 255 / np.max(UpperCamelCase_)

   __lowercase								=		np.sqrt((np.square(UpperCamelCase_)) + (np.square(UpperCamelCase_)))
   __lowercase								=		dst_xy * 255 / np.max(UpperCamelCase_)
   __lowercase								=		dst_xy.astype(np.uinta)

   __lowercase								=		np.arctana(UpperCamelCase_,     UpperCamelCase_)
   return dst, theta


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

   _a ,		_a					 =				sobel_filter(gray)

   # show result images
   imshow('sobel filter', sobel_grad)
   imshow('sobel theta', sobel_theta)
   waitKey(0)




