



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

import cva
import numpy as np

# Parrameters
lowercase  							=					(7_20, 12_80)  # Height, Width
lowercase  							=					(0.4, 0.6)  # if height or width lower than this scale, drop it.
lowercase  							=					1 / 1_00
lowercase  							=					''''''
lowercase  							=					''''''
lowercase  							=					''''''
lowercase  							=					2_50




def 	UpperCAmelCase     (		):

		'''simple docstring'''


		_UpperCAmelCase ,					_UpperCAmelCase							 =		get_dataset(A     ,				A       )
		for index in range(A       ):
				_UpperCAmelCase							 =		random.sample(range(len(A       )       )     ,				4       )
				_UpperCAmelCase ,					_UpperCAmelCase ,					_UpperCAmelCase							 =		update_image_and_anno(
				    A     ,				A     ,				A     ,				A     ,				A     ,				filter_scale=A     ,				)

				# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
				_UpperCAmelCase							 =		random_chars(32       )
				_UpperCAmelCase							 =		path.split(os.sep       )[-1].rsplit('.'     ,				1       )[0]
				_UpperCAmelCase							 =		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}'       )
				_UpperCAmelCase							 =		[]
				for anno in new_annos:
						_UpperCAmelCase							 =		anno[3] - anno[1]
						_UpperCAmelCase							 =		anno[4] - anno[2]
						_UpperCAmelCase							 =		anno[1] + width / 2
						_UpperCAmelCase							 =		anno[2] + height / 2
						_UpperCAmelCase							 =		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 	UpperCAmelCase     (		A	:						str     ,				A	:						str       ):

		'''simple docstring'''


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

				_UpperCAmelCase							 =		[]
				for obj_list in obj_lists:
						_UpperCAmelCase							 =		obj_list.rstrip('\n'       ).split(' '       )
						_UpperCAmelCase							 =		float(obj[1]       ) - float(obj[3]       ) / 2
						_UpperCAmelCase							 =		float(obj[2]       ) - float(obj[4]       ) / 2
						_UpperCAmelCase							 =		float(obj[1]       ) + float(obj[3]       ) / 2
						_UpperCAmelCase							 =		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 	UpperCAmelCase     (		A	:						list     ,				A	:						list     ,				A	:						list[int]     ,				A	:						tuple[int, int]     ,				A	:						tuple[float, float]     ,				A	:						float = 0.0     ,				):

		'''simple docstring'''


		_UpperCAmelCase							 =		np.zeros([output_size[0], output_size[1], 3]     ,				dtype=np.uinta       )
		_UpperCAmelCase							 =		scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
		_UpperCAmelCase							 =		scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
		_UpperCAmelCase							 =		int(scale_x * output_size[1]       )
		_UpperCAmelCase							 =		int(scale_y * output_size[0]       )

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

		'''simple docstring'''


		assert number_char > 1, "The number of character should greater than 1"
		_UpperCAmelCase							 =		ascii_lowercase + digits
		return "".join(random.choice(A       ) for _ in range(A       )       )


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







"""simple docstring"""





import os




def 	UpperCAmelCase     (		):

		'''simple docstring'''


		_UpperCAmelCase							 =		os.path.join(os.path.dirname(A       )     ,				'num.txt'       )
		with open(A       ) as file_hand:
				return str(sum(int(A       ) for line in file_hand       )       )[:10]


if __name__ == "__main__":
					print(solution())


