


import cva
import numpy as np




class A    :






      def __init__(   self		:	Tuple     ,  lowercase_		:	float     ,  lowercase_		:	int					)   ->		Optional[int]:
             """simple docstring"""




             if k in (0.04, 0.06):
                    _lowerCamelCase			:						Tuple            =k
                    _lowerCamelCase			:						int            =window_size
             else:
                    raise ValueError('invalid k value'					)






      def __str__(   self		:	Union[str, Any]					)   ->		str:
             """simple docstring"""




             return str(self.k					)






      def 			lowerCamelCase			(   self		:	str     ,  lowercase_		:	str					)   ->		tuple[cva.Mat, list[list[int]]]:
             """simple docstring"""




             _lowerCamelCase			:						List[str]            =cva.imread(lowercase_     ,  0					)
             _lowerCamelCase      ,	_lowerCamelCase			:						Optional[int]            =img.shape
             _lowerCamelCase			:						list[list[int]]            =[]
             _lowerCamelCase			:						int            =img.copy()
             _lowerCamelCase			:						Any            =cva.cvtColor(lowercase_     ,  cva.COLOR_GRAY2RGB					)
             _lowerCamelCase      ,	_lowerCamelCase			:						List[str]            =np.gradient(lowercase_					)
             _lowerCamelCase			:						Tuple            =dx**2
             _lowerCamelCase			:						List[Any]            =dy**2
             _lowerCamelCase			:						str            =dx * dy
             _lowerCamelCase			:						int            =0.04
             _lowerCamelCase			:						Optional[int]            =self.window_size // 2
             for y in range(lowercase_     ,  h - offset					):
                    for x in range(lowercase_     ,  w - offset					):
                           _lowerCamelCase			:						Any            =ixx[
                               y - offset : y + offset + 1, x - offset : x + offset + 1
                           ].sum()
                           _lowerCamelCase			:						List[Any]            =iyy[
                               y - offset : y + offset + 1, x - offset : x + offset + 1
                           ].sum()
                           _lowerCamelCase			:						Dict            =ixy[
                               y - offset : y + offset + 1, x - offset : x + offset + 1
                           ].sum()

                           _lowerCamelCase			:						int            =(wxx * wyy) - (wxy**2)
                           _lowerCamelCase			:						Optional[Any]            =wxx + wyy
                           _lowerCamelCase			:						Any            =det - k * (trace**2)
                           # Can change the value
                           if r > 0.5:
                                  corner_list.append([x, y, r]					)
                                  color_img.itemset((y, x, 0)     ,  0					)
                                  color_img.itemset((y, x, 1)     ,  0					)
                                  color_img.itemset((y, x, 2)     ,  255					)
             return color_img, corner_list


if __name__ == "__main__":
 lowerCamelCase		   =			HarrisCorner(0.04, 3)
 lowerCamelCase   ,							lowerCamelCase		   =			edge_detect.detect('path_to_image')
 cva.imwrite('detect.png', color_img)






import numpy as np




def       a_ (       SCREAMING_SNAKE_CASE__   : np.ndarray						,     SCREAMING_SNAKE_CASE__   : float	):
       '''simple docstring'''





       return np.where(vector > 0						,     SCREAMING_SNAKE_CASE__						,     (alpha * (np.exp(SCREAMING_SNAKE_CASE__	) - 1))	)


if __name__ == "__main__":
 import doctest

 doctest.testmod()


