


'''simple docstring'''

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

import cva
lowerCAmelCase      :int    	=			''''''
lowerCAmelCase      :str    	=			''''''
lowerCAmelCase      :Tuple    	=			''''''
lowerCAmelCase      :List[str]    	=			1  # (0 is vertical, 1 is horizontal)





def lowerCamelCase			(			):





	"""simple docstring"""







	__magic_name__       :    Union[str, Any]     	=     get_dataset(_UpperCAmelCase		,		_UpperCAmelCase		)
	print('Processing...'		)
	__magic_name__       :    List[Any]     	=     update_image_and_anno(_UpperCAmelCase		,		_UpperCAmelCase		,		_UpperCAmelCase		)

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





def lowerCamelCase			(			lowerCAmelCase				:	str		,		lowerCAmelCase				:	str		):





	"""simple docstring"""







	__magic_name__       :    Any     	=     []
	__magic_name__       :    Any     	=     []
	for label_file in glob.glob(os.path.join(_UpperCAmelCase		,		'*.txt'		)		):
		__magic_name__       :    Optional[Any]     	=     label_file.split(os.sep		)[-1].rsplit('.'		,		1		)[0]
		with open(_UpperCAmelCase		) as in_file:
			__magic_name__       :    List[str]     	=     in_file.readlines()
		__magic_name__       :    Optional[Any]     	=     os.path.join(_UpperCAmelCase		,		f'{label_name}.jpg'		)

		__magic_name__       :    str     	=     []
		for obj_list in obj_lists:
			__magic_name__       :    str     	=     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(_UpperCAmelCase		)
		labels.append(_UpperCAmelCase		)
	return img_paths, labels





def lowerCamelCase			(			lowerCAmelCase				:	list		,		lowerCAmelCase				:	list		,		lowerCAmelCase				:	int = 1		):





	"""simple docstring"""







	__magic_name__       :    Dict     	=     []
	__magic_name__       :    Optional[Any]     	=     []
	__magic_name__       :    Any     	=     []
	for idx in range(len(_UpperCAmelCase		)		):
		__magic_name__       :    Tuple     	=     []
		__magic_name__       :    List[Any]     	=     img_list[idx]
		path_list.append(_UpperCAmelCase		)
		__magic_name__       :    str     	=     anno_list[idx]
		__magic_name__       :    str     	=     cva.imread(_UpperCAmelCase		)
		if flip_type == 1:
			__magic_name__       :    Any     	=     cva.flip(_UpperCAmelCase		,		_UpperCAmelCase		)
			for bbox in img_annos:
				__magic_name__       :    List[str]     	=     1 - bbox[1]
				new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]		)
		elif flip_type == 0:
			__magic_name__       :    Any     	=     cva.flip(_UpperCAmelCase		,		_UpperCAmelCase		)
			for bbox in img_annos:
				__magic_name__       :    Union[str, Any]     	=     1 - bbox[2]
				new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]		)
		new_annos_lists.append(_UpperCAmelCase		)
		new_imgs_list.append(_UpperCAmelCase		)
	return new_imgs_list, new_annos_lists, path_list





def lowerCamelCase			(			lowerCAmelCase				:	int = 32		):





	"""simple docstring"""







	assert number_char > 1, "The number of character should greater than 1"
	__magic_name__       :    Union[str, Any]     	=     ascii_lowercase + digits
	return "".join(random.choice(_UpperCAmelCase		) for _ in range(_UpperCAmelCase		)		)


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




from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros

def        a						(      _UpperCAmelCase							:					Tuple ,   _UpperCAmelCase							:					Optional[int]						):







		'''simple docstring'''





		__UpperCAmelCase    :     Union[str, Any]													=	k_size // 2
		__UpperCAmelCase							,					__UpperCAmelCase    :     Optional[Any]													=	mgrid[0 - center : k_size - center, 0 - center : k_size - center]
		__UpperCAmelCase    :     Any													=	1 / (2 * pi * sigma) * exp(-(square(_UpperCAmelCase						) + square(_UpperCAmelCase						)) / (2 * square(_UpperCAmelCase						))						)
		return g

def        a						(      _UpperCAmelCase							:					Optional[int] ,   _UpperCAmelCase							:					Any ,   _UpperCAmelCase							:					List[Any]						):







		'''simple docstring'''





		__UpperCAmelCase							,					__UpperCAmelCase    :     Union[str, Any]													=	image.shape[0], image.shape[1]
		# dst image height and width
		__UpperCAmelCase    :     str													=	height - k_size + 1
		__UpperCAmelCase    :     Optional[int]													=	width - k_size + 1

		# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
		__UpperCAmelCase    :     str													=	zeros((dst_height * dst_width, k_size * k_size)						)
		__UpperCAmelCase    :     Optional[Any]													=	0
		for i, j in product(range(_UpperCAmelCase						) ,   range(_UpperCAmelCase						)						):
				__UpperCAmelCase    :     int													=	ravel(image[i : i + k_size, j : j + k_size]						)
				__UpperCAmelCase    :     Union[str, Any]													=	window
				row += 1

		#  turn the kernel into shape(k*k, 1)
		__UpperCAmelCase    :     Tuple													=	gen_gaussian_kernel(_UpperCAmelCase ,   _UpperCAmelCase						)
		__UpperCAmelCase    :     List[Any]													=	ravel(_UpperCAmelCase						)

		# reshape and get the dst image
		__UpperCAmelCase    :     Optional[Any]													=	dot(_UpperCAmelCase ,   _UpperCAmelCase						).reshape(_UpperCAmelCase ,   _UpperCAmelCase						).astype(_UpperCAmelCase						)

		return dst


if __name__ == "__main__":
				# read original image
				__A   			=imread(R"../image_data/lena.jpg")
				# turn image in gray scale value
				__A   			=cvtColor(img, COLOR_BGR2GRAY)

				# get values with two different mask size
				__A   			=gaussian_filter(gray, 3, sigma=1)
				__A   			=gaussian_filter(gray, 5, sigma=0.8)

				# show result images
				imshow("gaussian filter with 3x3 mask", gaussianaxa)
				imshow("gaussian filter with 5x5 mask", gaussianaxa)
				waitKey()





