


import doctest
from collections import deque

import numpy as np







class        UpperCamelCase__   :

					def __init__(     self       :   List[Any]       ):






										'''simple docstring'''






										lowercase_  							=			[2, 1, 2, -1]
										lowercase_  							=			[1, 2, 3, 4]







					def   UpperCAmelCase__       (     self       :   Any       ):






										'''simple docstring'''






										lowercase_  							=			len(self.first_signal       )
										lowercase_  							=			len(self.second_signal       )

										lowercase_  							=			max(UpperCamelCase__							,					UpperCamelCase__       )

										# create a zero matrix of max_length x max_length
										lowercase_  							=			[[0] * max_length for i in range(UpperCamelCase__       )]

										# fills the smaller signal with zeros to make both signals of same length
										if length_first_signal < length_second_signal:
															self.first_signal += [0] * (max_length - length_first_signal)
										elif length_first_signal > length_second_signal:
															self.second_signal += [0] * (max_length - length_second_signal)
										for i in range(UpperCamelCase__       ):
															lowercase_  							=			deque(self.second_signal       )
															rotated_signal.rotate(UpperCamelCase__       )
															for j, item in enumerate(UpperCamelCase__       ):
																				matrix[i][j] += item

        # multiply the matrix with the first signal
										lowercase_  							=			np.matmul(np.transpose(UpperCamelCase__       )							,					np.transpose(self.first_signal       )       )

										# rounding-off to two decimal places
										return [round(UpperCamelCase__							,					2       ) for i in final_signal]


if __name__ == "__main__":
							doctest.testmod()






import cva
import numpy as np







class        UpperCamelCase__   :

					def __init__(     self       :   List[str]							,					UpperCamelCase__       :   float							,					UpperCamelCase__       :   int       ):






										'''simple docstring'''






										if k in (0.04, 0.06):
															lowercase_  							=			k
															lowercase_  							=			window_size
										else:
															raise ValueError("""invalid k value"""       )

					def __str__(     self       :   Optional[int]       ):






										'''simple docstring'''






										return str(self.k       )







					def   UpperCAmelCase__       (     self       :   Optional[Any]							,					UpperCamelCase__       :   str       ):






										'''simple docstring'''






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

																				lowercase_  							=			(wxx * wyy) - (wxy**2)
																				lowercase_  							=			wxx + wyy
																				lowercase_  							=			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__":
							a					  =     HarrisCorner(0.04, 3)
							a  ,					a					  =     edge_detect.detect('path_to_image')
							cva.imwrite('detect.png', color_img)


