



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

import cva
UpperCAmelCase__       =	""
UpperCAmelCase__       =	""
UpperCAmelCase__       =	""
UpperCAmelCase__       =	1  # (0 is vertical, 1 is horizontal)





def 							A     (					)    ->			None:







			'''simple docstring'''
			_UpperCAmelCase	,					_UpperCAmelCase			=       get_dataset(_UpperCAmelCase							,       _UpperCAmelCase   )
			print('Processing...'   )
			_UpperCAmelCase	,					_UpperCAmelCase	,					_UpperCAmelCase			=       update_image_and_anno(_UpperCAmelCase							,       _UpperCAmelCase							,       _UpperCAmelCase   )

			for index, image in enumerate(_UpperCAmelCase   ):
						# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
						_UpperCAmelCase			=       random_chars(32   )
						_UpperCAmelCase			=       paths[index].split(os.sep   )[-1].rsplit('.'							,       1   )[0]
						_UpperCAmelCase			=       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}"   )
						_UpperCAmelCase			=       []
						for anno in new_annos[index]:
									_UpperCAmelCase			=       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 							A     (					_UpperCAmelCase    :       str							,       _UpperCAmelCase    :       str   )    ->			tuple[list, list]:







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

						_UpperCAmelCase			=       []
						for obj_list in obj_lists:
									_UpperCAmelCase			=       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 							A     (					_UpperCAmelCase    :       list							,       _UpperCAmelCase    :       list							,       _UpperCAmelCase    :       int = 1   )    ->			tuple[list, list, list]:







			'''simple docstring'''
			_UpperCAmelCase			=       []
			_UpperCAmelCase			=       []
			_UpperCAmelCase			=       []
			for idx in range(len(_UpperCAmelCase   )   ):
						_UpperCAmelCase			=       []
						_UpperCAmelCase			=       img_list[idx]
						path_list.append(_UpperCAmelCase   )
						_UpperCAmelCase			=       anno_list[idx]
						_UpperCAmelCase			=       cva.imread(_UpperCAmelCase   )
						if flip_type == 1:
									_UpperCAmelCase			=       cva.flip(_UpperCAmelCase							,       _UpperCAmelCase   )
									for bbox in img_annos:
												_UpperCAmelCase			=       1 - bbox[1]
												new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]   )
						elif flip_type == 0:
									_UpperCAmelCase			=       cva.flip(_UpperCAmelCase							,       _UpperCAmelCase   )
									for bbox in img_annos:
												_UpperCAmelCase			=       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 							A     (					_UpperCAmelCase    :       int = 32   )    ->			str:







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


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





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase__       =	{
    "configuration_clip": [
        "CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "CLIPConfig",
        "CLIPOnnxConfig",
        "CLIPTextConfig",
        "CLIPVisionConfig",
    ],
    "processing_clip": ["CLIPProcessor"],
    "tokenization_clip": ["CLIPTokenizer"],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	["CLIPTokenizerFast"]

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	["CLIPFeatureExtractor"]
							UpperCAmelCase__       =	["CLIPImageProcessor"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	[
							    "CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "CLIPModel",
							    "CLIPPreTrainedModel",
							    "CLIPTextModel",
							    "CLIPTextModelWithProjection",
							    "CLIPVisionModel",
							    "CLIPVisionModelWithProjection",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	[
							    "TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "TFCLIPModel",
							    "TFCLIPPreTrainedModel",
							    "TFCLIPTextModel",
							    "TFCLIPVisionModel",
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	[
							    "FlaxCLIPModel",
							    "FlaxCLIPPreTrainedModel",
							    "FlaxCLIPTextModel",
							    "FlaxCLIPTextPreTrainedModel",
							    "FlaxCLIPVisionModel",
							    "FlaxCLIPVisionPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_clip import (
							    CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    CLIPConfig,
							    CLIPOnnxConfig,
							    CLIPTextConfig,
							    CLIPVisionConfig,
							)
							from .processing_clip import CLIPProcessor
							from .tokenization_clip import CLIPTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_clip_fast import CLIPTokenizerFast

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_clip import CLIPFeatureExtractor
														from .image_processing_clip import CLIPImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_clip import (
														    CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    CLIPModel,
														    CLIPPreTrainedModel,
														    CLIPTextModel,
														    CLIPTextModelWithProjection,
														    CLIPVisionModel,
														    CLIPVisionModelWithProjection,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_clip import (
														    TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFCLIPModel,
														    TFCLIPPreTrainedModel,
														    TFCLIPTextModel,
														    TFCLIPVisionModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_clip import (
														    FlaxCLIPModel,
														    FlaxCLIPPreTrainedModel,
														    FlaxCLIPTextModel,
														    FlaxCLIPTextPreTrainedModel,
														    FlaxCLIPVisionModel,
														    FlaxCLIPVisionPreTrainedModel,
														)


else:
							import sys

							UpperCAmelCase__       =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
