


'''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

__SCREAMING_SNAKE_CASE				:							List[str]		       =		180







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







def 			a_							(  UpperCamelCase_	,     UpperCamelCase_	,     UpperCamelCase_   ):
							A_ 						=		np.zeros(UpperCamelCase_   )

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

																					if (
																					    0 <= direction < PI / 8
																					    or 1_5 * PI / 8 <= direction <= 2 * PI
																					    or 7 * PI / 8 <= direction <= 9 * PI / 8
																					):
																												A_ 						=		sobel_grad[row, col - 1]
																												A_ 						=		sobel_grad[row, col + 1]
																												if sobel_grad[row, col] >= w and sobel_grad[row, col] >= e:
																																			A_ 						=		sobel_grad[row, col]

																					elif (
																					    PI / 8 <= direction < 3 * PI / 8
																					    or 9 * PI / 8 <= direction < 1_1 * PI / 8
																					):
																												A_ 						=		sobel_grad[row + 1, col - 1]
																												A_ 						=		sobel_grad[row - 1, col + 1]
																												if sobel_grad[row, col] >= sw and sobel_grad[row, col] >= ne:
																																			A_ 						=		sobel_grad[row, col]

																					elif (
																					    3 * PI / 8 <= direction < 5 * PI / 8
																					    or 1_1 * PI / 8 <= direction < 1_3 * PI / 8
																					):
																												A_ 						=		sobel_grad[row - 1, col]
																												A_ 						=		sobel_grad[row + 1, col]
																												if sobel_grad[row, col] >= n and sobel_grad[row, col] >= s:
																																			A_ 						=		sobel_grad[row, col]

																					elif (
																					    5 * PI / 8 <= direction < 7 * PI / 8
																					    or 1_3 * PI / 8 <= direction < 1_5 * PI / 8
																					):
																												A_ 						=		sobel_grad[row - 1, col - 1]
																												A_ 						=		sobel_grad[row + 1, col + 1]
																												if sobel_grad[row, col] >= nw and sobel_grad[row, col] >= se:
																																			A_ 						=		sobel_grad[row, col]

							return destination







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







def 			a_							(  UpperCamelCase_	,     UpperCamelCase_	,     UpperCamelCase_	,     UpperCamelCase_   ):
							for row in range(1	,     image_shape[0]   ):
														for col in range(1	,     image_shape[1]   ):
																					if destination[row, col] == weak:
																												if 2_5_5 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],
																												):
																																			A_ 						=		strong
																												else:
																																			A_ 						=		0







def 			a_							(  UpperCamelCase_	,     UpperCamelCase_=1_5	,     UpperCamelCase_=3_0	,     UpperCamelCase_=1_2_8	,     UpperCamelCase_=2_5_5   ):
							# gaussian_filter
							A_ 						=		img_convolve(UpperCamelCase_	,     gen_gaussian_kernel(9	,     sigma=1.4   )   )
							# get the gradient and degree by sobel_filter
							A_						,				A_ 						=		sobel_filter(UpperCamelCase_   )
							A_ 						=		PI + np.radadeg(UpperCamelCase_   )

							A_ 						=		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				:							Any		       =		cva.imread(r'''../image_data/lena.jpg''', 0)
							# canny edge detection
							__SCREAMING_SNAKE_CASE				:							Tuple		       =		canny(lena)
							cva.imshow('''canny''', canny_destination)
							cva.waitKey(0)









'''simple docstring'''
import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_with_pabee

from transformers.testing_utils import TestCasePlus


logging.basicConfig(level=logging.DEBUG)

__SCREAMING_SNAKE_CASE				:							str		       =		logging.getLogger()







def 			a_							(  ):
							A_ 						=		argparse.ArgumentParser()
							parser.add_argument("-f"   )
							A_ 						=		parser.parse_args()
							return args.f







class 				__lowerCAmelCase      (      lowercase	):

						"""simple docstring"""






						def 							_UpperCAmelCase					(     self       :			List[Any]  ):
													A_ 						=		logging.StreamHandler(sys.stdout  )
													logger.addHandler(lowerCAmelCase  )

													A_ 						=		self.get_auto_remove_tmp_dir()
													A_ 						=		F"\n            run_glue_with_pabee.py\n            --model_type albert\n            --model_name_or_path albert-base-v2\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --task_name mrpc\n            --do_train\n            --do_eval\n            --per_gpu_train_batch_size=2\n            --per_gpu_eval_batch_size=1\n            --learning_rate=2e-5\n            --max_steps=50\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            ".split()

													with patch.object(lowerCAmelCase   ,     "argv"   ,     lowerCAmelCase  ):
																				A_ 						=		run_glue_with_pabee.main()
																				for value in result.values():
																											self.assertGreaterEqual(lowerCAmelCase   ,     0.7_5  )





