



"""simple docstring"""




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

import cva
import numpy as np

# Parrameters
lowerCAmelCase__		:					List[Any]							=(720, 1280)  # Height, Width
lowerCAmelCase__		:					Union[str, Any]							=(0.4, 0.6)  # if height or width lower than this scale, drop it.
lowerCAmelCase__		:					Union[str, Any]							=1 / 100
lowerCAmelCase__		:					int							=''''''
lowerCAmelCase__		:					List[Any]							=''''''
lowerCAmelCase__		:					List[str]							=''''''
lowerCAmelCase__		:					str							=250






def      __lowercase       (			)    ->			None:
							__SCREAMING_SNAKE_CASE							,	__SCREAMING_SNAKE_CASE									= get_dataset(a__							,       a__       )
							for index in range(a__       ):
														__SCREAMING_SNAKE_CASE									= random.sample(range(len(a__       )       )							,       4       )
														__SCREAMING_SNAKE_CASE							,	__SCREAMING_SNAKE_CASE							,	__SCREAMING_SNAKE_CASE									= update_image_and_anno(
														    a__							,       a__							,       a__							,       a__							,       a__							,       filter_scale=a__							,       )

														# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
														__SCREAMING_SNAKE_CASE									= random_chars(32       )
														__SCREAMING_SNAKE_CASE									= path.split(os.sep       )[-1].rsplit('.'							,       1       )[0]
														__SCREAMING_SNAKE_CASE									= f"""{OUTPUT_DIR}/{file_name}_MOSAIC_{letter_code}"""
														cva.imwrite(f"""{file_root}.jpg"""							,       a__							,       [cva.IMWRITE_JPEG_QUALITY, 85]       )
														print(f"""Succeeded {index+1}/{NUMBER_IMAGES} with {file_name}"""       )
														__SCREAMING_SNAKE_CASE									= []
														for anno in new_annos:
																					__SCREAMING_SNAKE_CASE									= anno[3] - anno[1]
																					__SCREAMING_SNAKE_CASE									= anno[4] - anno[2]
																					__SCREAMING_SNAKE_CASE									= anno[1] + width / 2
																					__SCREAMING_SNAKE_CASE									= anno[2] + height / 2
																					__SCREAMING_SNAKE_CASE									= f"""{anno[0]} {x_center} {y_center} {width} {height}"""
																					annos_list.append(a__       )
														with open(f"""{file_root}.txt"""							,       'w'       ) as outfile:
																					outfile.write('\n'.join(line for line in annos_list       )       )






def      __lowercase       (			a__							,       a__       )    ->			tuple[list, list]:
							__SCREAMING_SNAKE_CASE									= []
							__SCREAMING_SNAKE_CASE									= []
							for label_file in glob.glob(os.path.join(a__							,       '*.txt'       )       ):
														__SCREAMING_SNAKE_CASE									= label_file.split(os.sep       )[-1].rsplit('.'							,       1       )[0]
														with open(a__       ) as in_file:
																					__SCREAMING_SNAKE_CASE									= in_file.readlines()
														__SCREAMING_SNAKE_CASE									= os.path.join(a__							,       f"""{label_name}.jpg"""       )

														__SCREAMING_SNAKE_CASE									= []
														for obj_list in obj_lists:
																					__SCREAMING_SNAKE_CASE									= obj_list.rstrip('\n'       ).split(' '       )
																					__SCREAMING_SNAKE_CASE									= float(obj[1]       ) - float(obj[3]       ) / 2
																					__SCREAMING_SNAKE_CASE									= float(obj[2]       ) - float(obj[4]       ) / 2
																					__SCREAMING_SNAKE_CASE									= float(obj[1]       ) + float(obj[3]       ) / 2
																					__SCREAMING_SNAKE_CASE									= float(obj[2]       ) + float(obj[4]       ) / 2

																					boxes.append([int(obj[0]       ), xmin, ymin, xmax, ymax]       )
														if not boxes:
																					continue
														img_paths.append(a__       )
														labels.append(a__       )
							return img_paths, labels






def      __lowercase       (			a__							,       a__							,       a__							,       a__							,       a__							,       a__ = 0.0							,       )    ->			tuple[list, list, str]:
							__SCREAMING_SNAKE_CASE									= np.zeros([output_size[0], output_size[1], 3]							,       dtype=np.uinta       )
							__SCREAMING_SNAKE_CASE									= scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
							__SCREAMING_SNAKE_CASE									= scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
							__SCREAMING_SNAKE_CASE									= int(scale_x * output_size[1]       )
							__SCREAMING_SNAKE_CASE									= int(scale_y * output_size[0]       )

							__SCREAMING_SNAKE_CASE									= []
							__SCREAMING_SNAKE_CASE									= []
							for i, index in enumerate(a__       ):
														__SCREAMING_SNAKE_CASE									= all_img_list[index]
														path_list.append(a__       )
														__SCREAMING_SNAKE_CASE									= all_annos[index]
														__SCREAMING_SNAKE_CASE									= cva.imread(a__       )
														if i == 0:  # top-left
																					__SCREAMING_SNAKE_CASE									= cva.resize(a__							,       (divid_point_x, divid_point_y)       )
																					__SCREAMING_SNAKE_CASE									= img
																					for bbox in img_annos:
																												__SCREAMING_SNAKE_CASE									= bbox[1] * scale_x
																												__SCREAMING_SNAKE_CASE									= bbox[2] * scale_y
																												__SCREAMING_SNAKE_CASE									= bbox[3] * scale_x
																												__SCREAMING_SNAKE_CASE									= bbox[4] * scale_y
																												new_anno.append([bbox[0], xmin, ymin, xmax, ymax]       )
														elif i == 1:  # top-right
																					__SCREAMING_SNAKE_CASE									= cva.resize(a__							,       (output_size[1] - divid_point_x, divid_point_y)       )
																					__SCREAMING_SNAKE_CASE									= img
																					for bbox in img_annos:
																												__SCREAMING_SNAKE_CASE									= scale_x + bbox[1] * (1 - scale_x)
																												__SCREAMING_SNAKE_CASE									= bbox[2] * scale_y
																												__SCREAMING_SNAKE_CASE									= scale_x + bbox[3] * (1 - scale_x)
																												__SCREAMING_SNAKE_CASE									= bbox[4] * scale_y
																												new_anno.append([bbox[0], xmin, ymin, xmax, ymax]       )
														elif i == 2:  # bottom-left
																					__SCREAMING_SNAKE_CASE									= cva.resize(a__							,       (divid_point_x, output_size[0] - divid_point_y)       )
																					__SCREAMING_SNAKE_CASE									= img
																					for bbox in img_annos:
																												__SCREAMING_SNAKE_CASE									= bbox[1] * scale_x
																												__SCREAMING_SNAKE_CASE									= scale_y + bbox[2] * (1 - scale_y)
																												__SCREAMING_SNAKE_CASE									= bbox[3] * scale_x
																												__SCREAMING_SNAKE_CASE									= scale_y + bbox[4] * (1 - scale_y)
																												new_anno.append([bbox[0], xmin, ymin, xmax, ymax]       )
														else:  # bottom-right
																					__SCREAMING_SNAKE_CASE									= cva.resize(
																					    a__							,       (output_size[1] - divid_point_x, output_size[0] - divid_point_y)       )
																					__SCREAMING_SNAKE_CASE									= img
																					for bbox in img_annos:
																												__SCREAMING_SNAKE_CASE									= scale_x + bbox[1] * (1 - scale_x)
																												__SCREAMING_SNAKE_CASE									= scale_y + bbox[2] * (1 - scale_y)
																												__SCREAMING_SNAKE_CASE									= scale_x + bbox[3] * (1 - scale_x)
																												__SCREAMING_SNAKE_CASE									= scale_y + bbox[4] * (1 - scale_y)
																												new_anno.append([bbox[0], xmin, ymin, xmax, ymax]       )

    # Remove bounding box small than scale of filter
							if filter_scale > 0:
														__SCREAMING_SNAKE_CASE									= [
														    anno
														    for anno in new_anno
														    if filter_scale < (anno[3] - anno[1]) and filter_scale < (anno[4] - anno[2])
														]

							return output_img, new_anno, path_list[0]






def      __lowercase       (			a__       )    ->			str:
							assert number_char > 1, "The number of character should greater than 1"
							__SCREAMING_SNAKE_CASE									= ascii_lowercase + digits
							return "".join(random.choice(a__       ) for _ in range(a__       )       )


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











from ..utils import DummyObject, requires_backends

class        UpperCAmelCase_  (       metaclass=UpperCamelCase_	):

						'''simple docstring'''




						UpperCamelCase__      :			Optional[int]      =  ['''speech''']






						def __init__(   self				,							*_A				,							**_A		):







													'''simple docstring'''

													requires_backends(self				,							['speech']		)







class        UpperCAmelCase_  (       metaclass=UpperCamelCase_	):

						'''simple docstring'''




						UpperCamelCase__      :			Optional[int]      =  ['''speech''']






						def __init__(   self				,							*_A				,							**_A		):







													'''simple docstring'''

													requires_backends(self				,							['speech']		)






