






'''simple docstring'''


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

import cva
import numpy as np

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







def 	__magic_name__( ):
						'''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 	__magic_name__( _A						,      _A					):
						'''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 	__magic_name__( _A						,      _A						,      _A						,      _A						,      _A						,      _A = 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 	__magic_name__( _A					):
						'''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 inspect
import unittest
class    _SCREAMING_SNAKE_CASE							(		unittest.TestCase	):


			'''simple docstring'''





			def 				A      (   self							:						Tuple			)							->    Any:

									'''simple docstring'''







									try:
															import diffusers  # noqa: F401
									except ImportError:
															assert False







			def 				A      (   self							:						Optional[int]			)							->    Union[str, Any]:

									'''simple docstring'''







									import diffusers
									from diffusers.dependency_versions_table import deps

									UpperCamelCase__         = inspect.getmembers(lowercase ,      inspect.isclass			)

									for cls_name, cls_module in all_classes:
															if "dummy_" in cls_module.__module__:
																					for backend in cls_module._backends:
																											if backend == "k_diffusion":
																																	UpperCamelCase__         = """k-diffusion"""
																											elif backend == "invisible_watermark":
																																	UpperCamelCase__         = """invisible-watermark"""
																											assert backend in deps, f"{backend} is not in the deps table!"
