
'''simple docstring'''







from . import __version__

# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
    CLOUDFRONT_DISTRIB_PREFIX,
    CONFIG_NAME,
    DISABLE_TELEMETRY,
    DUMMY_INPUTS,
    DUMMY_MASK,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    FEATURE_EXTRACTOR_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_PREFIX,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    MODEL_CARD_NAME,
    MULTIPLE_CHOICE_DUMMY_INPUTS,
    PYTORCH_PRETRAINED_BERT_CACHE,
    PYTORCH_TRANSFORMERS_CACHE,
    S3_BUCKET_PREFIX,
    SENTENCEPIECE_UNDERLINE,
    SPIECE_UNDERLINE,
    TF2_WEIGHTS_NAME,
    TF_WEIGHTS_NAME,
    TORCH_FX_REQUIRED_VERSION,
    TRANSFORMERS_CACHE,
    TRANSFORMERS_DYNAMIC_MODULE_NAME,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    WEIGHTS_INDEX_NAME,
    WEIGHTS_NAME,
    ContextManagers,
    DummyObject,
    EntryNotFoundError,
    ExplicitEnum,
    ModelOutput,
    PaddingStrategy,
    PushToHubMixin,
    RepositoryNotFoundError,
    RevisionNotFoundError,
    TensorType,
    _LazyModule,
    add_code_sample_docstrings,
    add_end_docstrings,
    add_start_docstrings,
    add_start_docstrings_to_model_forward,
    cached_property,
    copy_func,
    default_cache_path,
    define_sagemaker_information,
    get_cached_models,
    get_file_from_repo,
    get_full_repo_name,
    get_torch_version,
    has_file,
    http_user_agent,
    is_apex_available,
    is_bsa_available,
    is_coloredlogs_available,
    is_datasets_available,
    is_detectrona_available,
    is_faiss_available,
    is_flax_available,
    is_ftfy_available,
    is_in_notebook,
    is_ipex_available,
    is_librosa_available,
    is_offline_mode,
    is_onnx_available,
    is_pandas_available,
    is_phonemizer_available,
    is_protobuf_available,
    is_psutil_available,
    is_pyanvml_available,
    is_pyctcdecode_available,
    is_pytesseract_available,
    is_pytorch_quantization_available,
    is_rjieba_available,
    is_sagemaker_dp_enabled,
    is_sagemaker_mp_enabled,
    is_scipy_available,
    is_sentencepiece_available,
    is_seqio_available,
    is_sklearn_available,
    is_soundfile_availble,
    is_spacy_available,
    is_speech_available,
    is_tensor,
    is_tensorflow_probability_available,
    is_tfaonnx_available,
    is_tf_available,
    is_timm_available,
    is_tokenizers_available,
    is_torch_available,
    is_torch_bfaa_available,
    is_torch_cuda_available,
    is_torch_fx_available,
    is_torch_fx_proxy,
    is_torch_mps_available,
    is_torch_tfaa_available,
    is_torch_tpu_available,
    is_torchaudio_available,
    is_training_run_on_sagemaker,
    is_vision_available,
    replace_return_docstrings,
    requires_backends,
    to_numpy,
    to_py_obj,
    torch_only_method,
)



'''simple docstring'''







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

import cva
lowercase					:							int   =      ""
lowercase					:							Union[str, Any]   =      ""
lowercase					:							Tuple   =      ""
lowercase					:							Optional[int]   =      1  # (0 is vertical, 1 is horizontal)







def        SCREAMING_SNAKE_CASE__			(     ) ->			None:
	_snake_case		,				_snake_case     		=	get_dataset(__A    ,       __A			)
	print('Processing...'			)
	_snake_case		,				_snake_case		,				_snake_case     		=	update_image_and_anno(__A    ,       __A    ,       __A			)

	for index, image in enumerate(__A			):
		# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
		_snake_case     		=	random_chars(32			)
		_snake_case     		=	paths[index].split(os.sep			)[-1].rsplit('.'    ,       1			)[0]
		_snake_case     		=	F'{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}'
		cva.imwrite(F'/{file_root}.jpg'    ,       __A    ,       [cva.IMWRITE_JPEG_QUALITY, 85]			)
		print(F'Success {index+1}/{len(__A			)} with {file_name}'			)
		_snake_case     		=	[]
		for anno in new_annos[index]:
			_snake_case     		=	F'{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}'
			annos_list.append(__A			)
		with open(F'/{file_root}.txt'    ,       'w'			) as outfile:
			outfile.write('\n'.join(line for line in annos_list			)			)







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

		_snake_case     		=	[]
		for obj_list in obj_lists:
			_snake_case     		=	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(__A			)
		labels.append(__A			)
	return img_paths, labels







def        SCREAMING_SNAKE_CASE__			(     __A    ,       __A    ,       __A = 1			) ->			tuple[list, list, list]:
	_snake_case     		=	[]
	_snake_case     		=	[]
	_snake_case     		=	[]
	for idx in range(len(__A			)			):
		_snake_case     		=	[]
		_snake_case     		=	img_list[idx]
		path_list.append(__A			)
		_snake_case     		=	anno_list[idx]
		_snake_case     		=	cva.imread(__A			)
		if flip_type == 1:
			_snake_case     		=	cva.flip(__A    ,       __A			)
			for bbox in img_annos:
				_snake_case     		=	1 - bbox[1]
				new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]			)
		elif flip_type == 0:
			_snake_case     		=	cva.flip(__A    ,       __A			)
			for bbox in img_annos:
				_snake_case     		=	1 - bbox[2]
				new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]			)
		new_annos_lists.append(__A			)
		new_imgs_list.append(__A			)
	return new_imgs_list, new_annos_lists, path_list







def        SCREAMING_SNAKE_CASE__			(     __A = 32			) ->			str:
	assert number_char > 1, "The number of character should greater than 1"
	_snake_case     		=	ascii_lowercase + digits
	return "".join(random.choice(__A			) for _ in range(__A			)			)


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

