



import cva
import numpy as np



class 	lowerCamelCase__      :




		'''simple docstring'''



		def __init__(self		,__lowerCamelCase		,__lowerCamelCase			)					->      int:

						"""simple docstring"""






						if k in (0.04, 0.06):
										lowerCAmelCase__					:    Optional[int]												=					k
										lowerCAmelCase__					:    int												=					window_size
						else:
										raise ValueError('''invalid k value'''			)



		def __str__(self			)					->      str:

						"""simple docstring"""






						return str(self.k			)



		def 		lowerCAmelCase__				(self		,__lowerCamelCase			)					->      tuple[cva.Mat, list[list[int]]]:

						"""simple docstring"""






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

														lowerCAmelCase__					:    List[str]												=					(wxx * wyy) - (wxy**2)
														lowerCAmelCase__					:    List[Any]												=					wxx + wyy
														lowerCAmelCase__					:    str												=					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)		,2_55			)
						return color_img, corner_list


if __name__ == "__main__":
							__snake_case    :		Union[str, Any]  =HarrisCorner(0.04, 3)
							__snake_case    :		Union[str, Any]  =edge_detect.detect('path_to_image')
							cva.imwrite('detect.png', color_img)






__snake_case    :		Any  ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

__snake_case    :		Tuple  =[{'type': 'code', 'content': INSTALL_CONTENT}]
__snake_case    :		Tuple  ={
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}

