

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

import cva
import numpy as np

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





def       __lowerCamelCase			(				):







							'''simple docstring'''






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

														# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
														snake_case_           =					random_chars(32   )
														snake_case_           =					path.split(os.sep   )[-1].rsplit('.'     ,							1   )[0]
														snake_case_           =					F'''{OUTPUT_DIR}/{file_name}_MOSAIC_{letter_code}'''
														cva.imwrite(F'''{file_root}.jpg'''     ,							UpperCamelCase__     ,							[cva.IMWRITE_JPEG_QUALITY, 85]   )
														print(F'''Succeeded {index+1}/{NUMBER_IMAGES} with {file_name}'''   )
														snake_case_           =					[]
														for anno in new_annos:
																					snake_case_           =					anno[3] - anno[1]
																					snake_case_           =					anno[4] - anno[2]
																					snake_case_           =					anno[1] + width / 2
																					snake_case_           =					anno[2] + height / 2
																					snake_case_           =					F'''{anno[0]} {x_center} {y_center} {width} {height}'''
																					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			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






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

														snake_case_           =					[]
														for obj_list in obj_lists:
																					snake_case_           =					obj_list.rstrip('\n'   ).split(' '   )
																					snake_case_           =					float(obj[1]   ) - float(obj[3]   ) / 2
																					snake_case_           =					float(obj[2]   ) - float(obj[4]   ) / 2
																					snake_case_           =					float(obj[1]   ) + float(obj[3]   ) / 2
																					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(UpperCamelCase__   )
														labels.append(UpperCamelCase__   )
							return img_paths, labels





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__ = 0.0     ,							):







							'''simple docstring'''






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

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







							'''simple docstring'''






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


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







from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL

from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
    fastaa_timesteps,
    smartaa_timesteps,
    smartaa_timesteps,
    smartaaa_timesteps,
    smartaaa_timesteps,
    superaa_timesteps,
    superaa_timesteps,
    superaaa_timesteps,
)







@dataclass
class 				lowercase       ( lowercase_    ):
				__SCREAMING_SNAKE_CASE      :				Union[List[PIL.Image.Image], np.ndarray]
				__SCREAMING_SNAKE_CASE      :				Optional[List[bool]]
				__SCREAMING_SNAKE_CASE      :				Optional[List[bool]]


try:
					if not (is_transformers_available() and is_torch_available()):
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
					from .pipeline_if import IFPipeline
					from .pipeline_if_imgaimg import IFImgaImgPipeline
					from .pipeline_if_imgaimg_superresolution import IFImgaImgSuperResolutionPipeline
					from .pipeline_if_inpainting import IFInpaintingPipeline
					from .pipeline_if_inpainting_superresolution import IFInpaintingSuperResolutionPipeline
					from .pipeline_if_superresolution import IFSuperResolutionPipeline
					from .safety_checker import IFSafetyChecker
					from .watermark import IFWatermarker




