




'''simple docstring'''


import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey



def  _SCREAMING_SNAKE_CASE     (      UpperCamelCase__    :					int ,    UpperCamelCase__    :					int ,    UpperCamelCase__    :					int ,    UpperCamelCase__    :					int ,    UpperCamelCase__    :					int ,    UpperCamelCase__    :					int				):




     """simple docstring"""


     if (ksize % 2) == 0:
          a_     :							int     						=  ksize + 1
     a_     :							Any     						=  np.zeros((ksize, ksize) ,    dtype=np.floataa				)

     # each value
     for y in range(UpperCamelCase__				):
          for x in range(UpperCamelCase__				):
               # distance from center
               a_     :							List[str]     						=  x - ksize // 2
               a_     :							Optional[int]     						=  y - ksize // 2

               # degree to radiant
               a_     :							int     						=  theta / 180 * np.pi
               a_     :							Any     						=  np.cos(_theta				)
               a_     :							Any     						=  np.sin(_theta				)

               # get kernel x
               a_     :							Tuple     						=  cos_theta * px + sin_theta * py

               # get kernel y
               a_     :							Optional[Any]     						=  -sin_theta * px + cos_theta * py

               # fill kernel
               a_     :							Union[str, Any]     						=  np.exp(
                   -(_x**2 + gamma**2 * _y**2) / (2 * sigma**2)				) * np.cos(2 * np.pi * _x / lambd + psi				)

     return gabor


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 # read original image
 lowerCAmelCase_      :  Union[str, Any]				     =  imread('../image_data/lena.jpg')
 # turn image in gray scale value
 lowerCAmelCase_      :  Optional[int]				     =  cvtColor(img, COLOR_BGR2GRAY)

 # Apply multiple Kernel to detect edges
 lowerCAmelCase_      :  Optional[Any]				     =  np.zeros(gray.shape[:2])
 for theta in [0, 30, 60, 90, 120, 150]:
  lowerCAmelCase_      :  int				     =  gabor_filter_kernel(10, 8, theta, 10, 0, 0)
  out += filteraD(gray, CV_8UC3, kernel_aa)
 lowerCAmelCase_      :  Optional[Any]				     =  out / out.max() * 255
 lowerCAmelCase_      :  List[Any]				     =  out.astype(np.uinta)

 imshow('Original', gray)
 imshow('Gabor filter with 20x20 mask and 6 directions', out)

 waitKey(0)






'''simple docstring'''


from ..utils import DummyObject, requires_backends







class      SCREAMING_SNAKE_CASE    (						metaclass=snake_case_				):
      __magic_name__  :       Dict   							=					['''transformers''', '''torch''', '''note_seq''']






      def __init__( self   :  List[str]						,						*lowercase__   :  Dict						,						**lowercase__   :  int       ):


           '''simple docstring'''

           requires_backends(self						,						["""transformers""", """torch""", """note_seq"""]       )






      @classmethod
      def 							lowercase_						( cls   :  Dict						,						*lowercase__   :  List[str]						,						**lowercase__   :  str       ):


           '''simple docstring'''

           requires_backends(cls						,						["""transformers""", """torch""", """note_seq"""]       )






      @classmethod
      def 							lowercase_						( cls   :  str						,						*lowercase__   :  Optional[int]						,						**lowercase__   :  Any       ):


           '''simple docstring'''

           requires_backends(cls						,						["""transformers""", """torch""", """note_seq"""]       )
