





import cva
import numpy as np

from digital_image_processing.filters.convolve import img_convolve
from digital_image_processing.filters.sobel_filter import sobel_filter

_UpperCAmelCase										=					1_8_0




def 			lowerCAmelCase_			(				UpperCamelCase_       ,		UpperCamelCase_	)  ->		List[str]:
       UpperCamelCase_ 							=	k_size // 2
       UpperCamelCase_							,			UpperCamelCase_ 							=	np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
       UpperCamelCase_ 							=	(
           1
           / (2 * np.pi * sigma)
           * np.exp(-(np.square(UpperCamelCase_	) + np.square(UpperCamelCase_	)) / (2 * np.square(UpperCamelCase_	))	)
       )
       return g




def 			lowerCAmelCase_			(				UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_	)  ->		Tuple:
       UpperCamelCase_ 							=	np.zeros(UpperCamelCase_	)

       for row in range(1       ,		image_shape[0] - 1	):
              for col in range(1       ,		image_shape[1] - 1	):
                     UpperCamelCase_ 							=	gradient_direction[row, col]

                     if (
                         0 <= direction < PI / 8
                         or 15 * PI / 8 <= direction <= 2 * PI
                         or 7 * PI / 8 <= direction <= 9 * PI / 8
                     ):
                            UpperCamelCase_ 							=	sobel_grad[row, col - 1]
                            UpperCamelCase_ 							=	sobel_grad[row, col + 1]
                            if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
                                   UpperCamelCase_ 							=	sobel_grad[row, col]

                     elif (
                         PI / 8 <= direction < 3 * PI / 8
                         or 9 * PI / 8 <= direction < 11 * PI / 8
                     ):
                            UpperCamelCase_ 							=	sobel_grad[row + 1, col - 1]
                            UpperCamelCase_ 							=	sobel_grad[row - 1, col + 1]
                            if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
                                   UpperCamelCase_ 							=	sobel_grad[row, col]

                     elif (
                         3 * PI / 8 <= direction < 5 * PI / 8
                         or 11 * PI / 8 <= direction < 13 * PI / 8
                     ):
                            UpperCamelCase_ 							=	sobel_grad[row - 1, col]
                            UpperCamelCase_ 							=	sobel_grad[row + 1, col]
                            if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
                                   UpperCamelCase_ 							=	sobel_grad[row, col]

                     elif (
                         5 * PI / 8 <= direction < 7 * PI / 8
                         or 13 * PI / 8 <= direction < 15 * PI / 8
                     ):
                            UpperCamelCase_ 							=	sobel_grad[row - 1, col - 1]
                            UpperCamelCase_ 							=	sobel_grad[row + 1, col + 1]
                            if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
                                   UpperCamelCase_ 							=	sobel_grad[row, col]

       return destination




def 			lowerCAmelCase_			(				UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_	)  ->		Tuple:
       for row in range(1       ,		image_shape[0] - 1	):
              for col in range(1       ,		image_shape[1] - 1	):
                     if destination[row, col] >= threshold_high:
                            UpperCamelCase_ 							=	strong
                     elif destination[row, col] <= threshold_low:
                            UpperCamelCase_ 							=	0
                     else:
                            UpperCamelCase_ 							=	weak




def 			lowerCAmelCase_			(				UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_	)  ->		int:
       for row in range(1       ,		image_shape[0]	):
              for col in range(1       ,		image_shape[1]	):
                     if destination[row, col] == weak:
                            if 255 in (
                                destination[row, col + 1],
                                destination[row, col - 1],
                                destination[row - 1, col],
                                destination[row + 1, col],
                                destination[row - 1, col - 1],
                                destination[row + 1, col - 1],
                                destination[row - 1, col + 1],
                                destination[row + 1, col + 1],
                            ):
                                   UpperCamelCase_ 							=	strong
                            else:
                                   UpperCamelCase_ 							=	0




def 			lowerCAmelCase_			(				UpperCamelCase_       ,		UpperCamelCase_=15       ,		UpperCamelCase_=30       ,		UpperCamelCase_=128       ,		UpperCamelCase_=255	)  ->		Union[str, Any]:
       # gaussian_filter
       UpperCamelCase_ 							=	img_convolve(UpperCamelCase_       ,		gen_gaussian_kernel(9       ,		sigma=1.4	)	)
       # get the gradient and degree by sobel_filter
       UpperCamelCase_							,			UpperCamelCase_ 							=	sobel_filter(UpperCamelCase_	)
       UpperCamelCase_ 							=	PI + np.radadeg(UpperCamelCase_	)

       UpperCamelCase_ 							=	suppress_non_maximum(image.shape       ,		UpperCamelCase_       ,		UpperCamelCase_	)

       detect_high_low_threshold(
           image.shape       ,		UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_	)

       track_edge(image.shape       ,		UpperCamelCase_       ,		UpperCamelCase_       ,		UpperCamelCase_	)

       return destination


if __name__ == "__main__":
     # read original image in gray mode
     _UpperCAmelCase										=					cva.imread(r'../image_data/lena.jpg', 0)
     # canny edge detection
     _UpperCAmelCase										=					canny(lena)
     cva.imshow('canny', canny_destination)
     cva.waitKey(0)




"""simple docstring"""



from __future__ import annotations





def 			_snake_case  (     UpperCAmelCase_	:       list[list[int]]       , UpperCAmelCase_	:       list[list[int]]      ):
     assert len(UpperCAmelCase_      ) == len(UpperCAmelCase_      )

     A__				      =	len(UpperCAmelCase_      )
     A__				      =	list(range(UpperCAmelCase_      )      )
     A__				      =	[-1] * n  # who the donor has donated to
     A__				      =	[-1] * n  # who the recipient has received from
     A__				      =	[0] * n

     while unmatched_donors:
          A__				      =	unmatched_donors[0]
          A__				      =	donor_pref[donor]
          A__				      =	donor_preference[num_donations[donor]]
          num_donations[donor] += 1
          A__				      =	recipient_pref[recipient]
          A__				      =	rec_record[recipient]

          if prev_donor != -1:
               if rec_preference.index(UpperCAmelCase_      ) > rec_preference.index(UpperCAmelCase_      ):
                    A__				      =	donor
                    A__				      =	recipient
                    unmatched_donors.append(UpperCAmelCase_      )
                    unmatched_donors.remove(UpperCAmelCase_      )
          else:
               A__				      =	donor
               A__				      =	recipient
               unmatched_donors.remove(UpperCAmelCase_      )
     return donor_record






