
'''simple docstring'''







import glob
import os
import random
from string import ascii_lowercase, digits

import cva
_snake_case				:   List[Any]     =				""""""
_snake_case				:   Union[str, Any]     =				""""""
_snake_case				:   int     =				""""""
_snake_case				:   Optional[Any]     =				1  # (0 is vertical, 1 is horizontal)



def 			_a		(	):
						_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE				= get_dataset(_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE  )
						print("Processing..."  )
						_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE				= update_image_and_anno(_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE  )

						for index, image in enumerate(_SCREAMING_SNAKE_CASE  ):
												# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
												_SCREAMING_SNAKE_CASE				= random_chars(32  )
												_SCREAMING_SNAKE_CASE				= paths[index].split(os.sep  )[-1].rsplit("."	,			1  )[0]
												_SCREAMING_SNAKE_CASE				= F'{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}'
												cva.imwrite(F'/{file_root}.jpg'	,			_SCREAMING_SNAKE_CASE	,			[cva.IMWRITE_JPEG_QUALITY, 85]  )
												print(F'Success {index+1}/{len(_SCREAMING_SNAKE_CASE  )} with {file_name}'  )
												_SCREAMING_SNAKE_CASE				= []
												for anno in new_annos[index]:
																		_SCREAMING_SNAKE_CASE				= F'{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}'
																		annos_list.append(_SCREAMING_SNAKE_CASE  )
												with open(F'/{file_root}.txt'	,			"w"  ) as outfile:
																		outfile.write("\n".join(line for line in annos_list  )  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str	,			_SCREAMING_SNAKE_CASE		:   str  ):
						_SCREAMING_SNAKE_CASE				= []
						_SCREAMING_SNAKE_CASE				= []
						for label_file in glob.glob(os.path.join(_SCREAMING_SNAKE_CASE	,			"*.txt"  )  ):
												_SCREAMING_SNAKE_CASE				= label_file.split(os.sep  )[-1].rsplit("."	,			1  )[0]
												with open(_SCREAMING_SNAKE_CASE  ) as in_file:
																		_SCREAMING_SNAKE_CASE				= in_file.readlines()
												_SCREAMING_SNAKE_CASE				= os.path.join(_SCREAMING_SNAKE_CASE	,			F'{label_name}.jpg'  )

												_SCREAMING_SNAKE_CASE				= []
												for obj_list in obj_lists:
																		_SCREAMING_SNAKE_CASE				= obj_list.rstrip("\n"  ).split(" "  )
																		boxes.append(
																		    [
																		        int(obj[0]  ),
																		        float(obj[1]  ),
																		        float(obj[2]  ),
																		        float(obj[3]  ),
																		        float(obj[4]  ),
																		    ]  )
												if not boxes:
																		continue
												img_paths.append(_SCREAMING_SNAKE_CASE  )
												labels.append(_SCREAMING_SNAKE_CASE  )
						return img_paths, labels



def 			_a		(	_SCREAMING_SNAKE_CASE		:   list	,			_SCREAMING_SNAKE_CASE		:   list	,			_SCREAMING_SNAKE_CASE		:   int = 1  ):
						_SCREAMING_SNAKE_CASE				= []
						_SCREAMING_SNAKE_CASE				= []
						_SCREAMING_SNAKE_CASE				= []
						for idx in range(len(_SCREAMING_SNAKE_CASE  )  ):
												_SCREAMING_SNAKE_CASE				= []
												_SCREAMING_SNAKE_CASE				= img_list[idx]
												path_list.append(_SCREAMING_SNAKE_CASE  )
												_SCREAMING_SNAKE_CASE				= anno_list[idx]
												_SCREAMING_SNAKE_CASE				= cva.imread(_SCREAMING_SNAKE_CASE  )
												if flip_type == 1:
																		_SCREAMING_SNAKE_CASE				= cva.flip(_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE  )
																		for bbox in img_annos:
																								_SCREAMING_SNAKE_CASE				= 1 - bbox[1]
																								new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]  )
												elif flip_type == 0:
																		_SCREAMING_SNAKE_CASE				= cva.flip(_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE  )
																		for bbox in img_annos:
																								_SCREAMING_SNAKE_CASE				= 1 - bbox[2]
																								new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]  )
												new_annos_lists.append(_SCREAMING_SNAKE_CASE  )
												new_imgs_list.append(_SCREAMING_SNAKE_CASE  )
						return new_imgs_list, new_annos_lists, path_list



def 			_a		(	_SCREAMING_SNAKE_CASE		:   int = 32  ):
						assert number_char > 1, "The number of character should greater than 1"
						_SCREAMING_SNAKE_CASE				= ascii_lowercase + digits
						return "".join(random.choice(_SCREAMING_SNAKE_CASE  ) for _ in range(_SCREAMING_SNAKE_CASE  )  )


if __name__ == "__main__":
						main()
						print("""DONE ✅""")

'''simple docstring'''







from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean



def 			_a		(	_SCREAMING_SNAKE_CASE		:   int  ):

						# A local function to see if a dot lands in the circle.
						def is_in_circle(_SCREAMING_SNAKE_CASE		:   float	,			_SCREAMING_SNAKE_CASE		:   float  ) -> bool:
												_SCREAMING_SNAKE_CASE				= sqrt((x**2) + (y**2)  )
												# Our circle has a radius of 1, so a distance
												# greater than 1 would land outside the circle.
												return distance_from_centre <= 1

						# The proportion of guesses that landed in the circle
						_SCREAMING_SNAKE_CASE				= mean(
						    int(is_in_circle(uniform(-1.0	,			1.0  )	,			uniform(-1.0	,			1.0  )  )  )
						    for _ in range(_SCREAMING_SNAKE_CASE  )  )
						# The ratio of the area for circle to square is pi/4.
						_SCREAMING_SNAKE_CASE				= proportion * 4
						print(F'The estimated value of pi is {pi_estimate}'  )
						print(F'The numpy value of pi is {pi}'  )
						print(F'The total error is {abs(pi - pi_estimate  )}'  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   int	,			_SCREAMING_SNAKE_CASE		:   Callable[[float], float]	,			_SCREAMING_SNAKE_CASE		:   float = 0.0	,			_SCREAMING_SNAKE_CASE		:   float = 1.0	,			):
						return mean(
						    function_to_integrate(uniform(_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE  )  ) for _ in range(_SCREAMING_SNAKE_CASE  )  ) * (max_value - min_value)



def 			_a		(	_SCREAMING_SNAKE_CASE		:   int	,			_SCREAMING_SNAKE_CASE		:   float = 0.0	,			_SCREAMING_SNAKE_CASE		:   float = 1.0  ):

						def identity_function(_SCREAMING_SNAKE_CASE		:   float  ) -> float:
												return x

						_SCREAMING_SNAKE_CASE				= area_under_curve_estimator(
						    _SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= (max_value * max_value - min_value * min_value) / 2

						print("******************"  )
						print(F'Estimating area under y=x where x varies from {min_value} to {max_value}'  )
						print(F'Estimated value is {estimated_value}'  )
						print(F'Expected value is {expected_value}'  )
						print(F'Total error is {abs(estimated_value - expected_value  )}'  )
						print("******************"  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   int  ):

						def function_to_integrate(_SCREAMING_SNAKE_CASE		:   float  ) -> float:
												return sqrt(4.0 - x * x  )

						_SCREAMING_SNAKE_CASE				= area_under_curve_estimator(
						    _SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE	,			0.0	,			2.0  )

						print("******************"  )
						print("Estimating pi using area_under_curve_estimator"  )
						print(F'Estimated value is {estimated_value}'  )
						print(F'Expected value is {pi}'  )
						print(F'Total error is {abs(estimated_value - pi  )}'  )
						print("******************"  )


if __name__ == "__main__":
						import doctest

						doctest.testmod()