'''simple docstring'''




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

_lowercase		:					List[str]													=		180




def 				lowerCamelCase      ( UpperCAmelCase__			:   List[Any] , UpperCAmelCase__			:   Optional[int]					)     -> List[Any]:
							lowercase_   :     Dict									=			k_size // 2
							lowercase_		,		lowercase_   :     Any									=			np.mgrid[0 - center : k_size - center, 0 - center : k_size - center]
							lowercase_   :     Union[str, Any]									=			(
							    1
							    / (2 * np.pi * sigma)
							    * np.exp(-(np.square(UpperCAmelCase__					) + np.square(UpperCAmelCase__					)) / (2 * np.square(UpperCAmelCase__					))					)
							)
							return g




def 				lowerCamelCase      ( UpperCAmelCase__			:   Dict , UpperCAmelCase__			:   Union[str, Any] , UpperCAmelCase__			:   int					)     -> List[Any]:
							lowercase_   :     str									=			np.zeros(UpperCAmelCase__					)

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

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

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

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

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

							return destination




def 				lowerCamelCase      ( UpperCAmelCase__			:   List[str] , UpperCAmelCase__			:   Optional[int] , UpperCAmelCase__			:   Any , UpperCAmelCase__			:   Any , UpperCAmelCase__			:   List[Any] , UpperCAmelCase__			:   int					)     -> Optional[Any]:
							for row in range(1 , image_shape[0] - 1					):
														for col in range(1 , image_shape[1] - 1					):
																					if destination[row, col] >= threshold_high:
																												lowercase_   :     List[Any]									=			strong
																					elif destination[row, col] <= threshold_low:
																												lowercase_   :     Optional[Any]									=			0
																					else:
																												lowercase_   :     Tuple									=			weak




def 				lowerCamelCase      ( UpperCAmelCase__			:   Any , UpperCAmelCase__			:   Tuple , UpperCAmelCase__			:   Tuple , UpperCAmelCase__			:   Optional[int]					)     -> Optional[Any]:
							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],
																												):
																																			lowercase_   :     Union[str, Any]									=			strong
																												else:
																																			lowercase_   :     str									=			0




def 				lowerCamelCase      ( UpperCAmelCase__			:   List[Any] , UpperCAmelCase__			:   Dict=15 , UpperCAmelCase__			:   str=30 , UpperCAmelCase__			:   Optional[Any]=128 , UpperCAmelCase__			:   List[Any]=255					)     -> Optional[int]:
							# gaussian_filter
							lowercase_   :     Tuple									=			img_convolve(UpperCAmelCase__ , gen_gaussian_kernel(9 , sigma=1.4					)					)
							# get the gradient and degree by sobel_filter
							lowercase_		,		lowercase_   :     Optional[int]									=			sobel_filter(UpperCAmelCase__					)
							lowercase_   :     str									=			PI + np.radadeg(UpperCAmelCase__					)

							lowercase_   :     List[Any]									=			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
						_lowercase		:					Dict													=		cva.imread(r"../image_data/lena.jpg", 0)
						# canny edge detection
						_lowercase		:					Any													=		canny(lena)
						cva.imshow("canny", canny_destination)
						cva.waitKey(0)






'''simple docstring'''




import os
import unittest

import pytest
from parameterized import parameterized

from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device


# skipping in unittest tests

_lowercase		:					int													=		[(1,)]




def 				lowerCamelCase      ( )     -> Dict:
							lowercase_   :     Union[str, Any]									=			bool(os.getenv("""RUN_SLOW""" , 0					)					)
							if run_slow:
														assert True
							else:
														assert False, "should have been skipped"




def 				lowerCamelCase      ( )     -> List[str]:
							lowercase_   :     Union[str, Any]									=			bool(os.getenv("""RUN_SLOW""" , 0					)					)
							if run_slow and torch_device == "cuda":
														assert True
							else:
														assert False, "should have been skipped"





@require_torch
class        __magic_name__		(       unittest.TestCase):







			@slow
			@require_torch_gpu
			def       SCREAMING_SNAKE_CASE_	(      self							:    Dict       ):
										check_slow_torch_cuda()







			@require_torch_gpu
			@slow
			def       SCREAMING_SNAKE_CASE_	(      self							:    List[str]       ):
										check_slow_torch_cuda()







			@parameterized.expand(lowercase_       )
			@slow
			def       SCREAMING_SNAKE_CASE_	(      self							:    Tuple							,     lowercase_							:    Dict=None       ):
										check_slow()




@slow
@require_torch_gpu
def 				lowerCamelCase      ( )     -> Union[str, Any]:
							check_slow_torch_cuda()




@require_torch_gpu
@slow
def 				lowerCamelCase      ( )     -> Any:
							check_slow_torch_cuda()




@slow
@pytest.mark.parametrize("""param""" , [1]					)
def 				lowerCamelCase      ( UpperCAmelCase__			:   List[str]					)     -> List[Any]:
							check_slow()




@pytest.mark.parametrize("""param""" , [1]					)
@slow
def 				lowerCamelCase      ( UpperCAmelCase__			:   Optional[Any]					)     -> Any:
							check_slow()





