





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

_SCREAMING_SNAKE_CASE   						=		1_80


def 				SCREAMING_SNAKE_CASE__    (     __a ,			__a ):
	snake_case_		:      List[Any]           =						k_size // 2
	snake_case_    ,snake_case_		:      Union[str, Any]           =						np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
	snake_case_		:      Union[str, Any]           =						(
	    1
	    / (2 * np.pi * sigma)
	    * np.exp(-(np.square(__UpperCamelCase ) + np.square(__UpperCamelCase )) / (2 * np.square(__UpperCamelCase )) )
	)
	return g


def 				SCREAMING_SNAKE_CASE__    (     __a ,			__a ,			__a ):
	snake_case_		:      List[Any]           =						np.zeros(__UpperCamelCase )

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

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

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

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

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

	return destination


def 				SCREAMING_SNAKE_CASE__    (     __a ,			__a ,			__a ,			__a ,			__a ,			__a ):


	for row in range(1 ,			image_shape[0] - 1 ):
		for col in range(1 ,			image_shape[1] - 1 ):
			if destination[row, col] >= threshold_high:
				snake_case_		:      Optional[Any]           =						strong
			elif destination[row, col] <= threshold_low:
				snake_case_		:      Optional[int]           =						0
			else:
				snake_case_		:      Optional[Any]           =						weak


def 				SCREAMING_SNAKE_CASE__    (     __a ,			__a ,			__a ,			__a ):


	for row in range(1 ,			image_shape[0] ):
		for col in range(1 ,			image_shape[1] ):
			if destination[row, col] == weak:
				if 2_55 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],
				):
					snake_case_		:      Union[str, Any]           =						strong
				else:
					snake_case_		:      int           =						0


def 				SCREAMING_SNAKE_CASE__    (     __a ,			__a=15 ,			__a=30 ,			__a=1_28 ,			__a=2_55 ):
	snake_case_		:      Dict           =						img_convolve(__UpperCamelCase ,			gen_gaussian_kernel(9 ,			sigma=1.4 ) )
	# get the gradient and degree by sobel_filter
	snake_case_    ,snake_case_		:      Optional[Any]           =						sobel_filter(__UpperCamelCase )
	snake_case_		:      Union[str, Any]           =						PI + np.radadeg(__UpperCamelCase )

	snake_case_		:      List[str]           =						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
						_SCREAMING_SNAKE_CASE   						=		cva.imread(R"""../image_data/lena.jpg""", 0)
						# canny edge detection
						_SCREAMING_SNAKE_CASE   						=		canny(lena)
						cva.imshow("""canny""", canny_destination)
						cva.waitKey(0)


"""simple docstring"""

class 		_lowercase :



						"""simple docstring"""




						def __init__(				self							:    List[str]     , UpperCamelCase__							:    int				)				->				None:
													'''simple docstring'''



													__UpperCamelCase							=data
													__UpperCamelCase							=None
													__UpperCamelCase							=None






def    lowerCAmelCase			(__UpperCamelCase							:    BinaryTreeNode | None							,					__UpperCamelCase							:    int			):
							"""simple docstring"""


							if node is None:
														__UpperCamelCase							=BinaryTreeNode(__UpperCamelCase			)
														return node

							# binary search tree is not empty,
							# so we will insert it into the tree
							# if new_value is less than value of data in node,
							#  add it to left subtree and proceed recursively
							if new_value < node.data:
														__UpperCamelCase							=insert(node.left_child							,					__UpperCamelCase			)
							else:
														# if new_value is greater than value of data in node,
														#  add it to right subtree and proceed recursively
														__UpperCamelCase							=insert(node.right_child							,					__UpperCamelCase			)
							return node


def    lowerCAmelCase			(__UpperCamelCase							:    None | BinaryTreeNode			):  # if node is None,return
							"""simple docstring"""


							if node:
														__UpperCamelCase							=inorder(node.left_child			)
														__UpperCamelCase							=[*inorder_array, node.data]
														__UpperCamelCase							=inorder_array + inorder(node.right_child			)
							else:
														__UpperCamelCase							=[]
							return inorder_array


def    lowerCAmelCase			():
							"""simple docstring"""


							__UpperCamelCase							=insert(__UpperCamelCase							,					1_5			)
							insert(__UpperCamelCase							,					1_0			)
							insert(__UpperCamelCase							,					2_5			)
							insert(__UpperCamelCase							,					6			)
							insert(__UpperCamelCase							,					1_4			)
							insert(__UpperCamelCase							,					2_0			)
							insert(__UpperCamelCase							,					6_0			)
							return root


def    lowerCAmelCase			():
							"""simple docstring"""


							__UpperCamelCase							=make_tree()
							print('''Printing values of binary search tree in Inorder Traversal.'''			)
							inorder(__UpperCamelCase			)


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()



