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

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



def 							lowerCamelCase_	( ):
				A_						,       A_													=	get_dataset(_lowercase			,    _lowercase  )
				print('''Processing...'''  )
				A_						,       A_						,       A_													=	update_image_and_anno(_lowercase			,    _lowercase			,    _lowercase  )

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



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

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



def 							lowerCamelCase_	( __UpperCamelCase			,    __UpperCamelCase			,    __UpperCamelCase = 1  ):
				A_													=	[]
				A_													=	[]
				A_													=	[]
				for idx in range(len(_lowercase  )  ):
								A_													=	[]
								A_													=	img_list[idx]
								path_list.append(_lowercase  )
								A_													=	anno_list[idx]
								A_													=	cva.imread(_lowercase  )
								if flip_type == 1:
												A_													=	cva.flip(_lowercase			,    _lowercase  )
												for bbox in img_annos:
																A_													=	1 - bbox[1]
																new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]  )
								elif flip_type == 0:
												A_													=	cva.flip(_lowercase			,    _lowercase  )
												for bbox in img_annos:
																A_													=	1 - bbox[2]
																new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]  )
								new_annos_lists.append(_lowercase  )
								new_imgs_list.append(_lowercase  )
				return new_imgs_list, new_annos_lists, path_list



def 							lowerCamelCase_	( __UpperCamelCase = 32  ):
				assert number_char > 1, "The number of character should greater than 1"
				A_													=	ascii_lowercase + digits
				return "".join(random.choice(_lowercase  ) for _ in range(_lowercase  )  )


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



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__snake_case   							=						logging.get_logger(__name__)

__snake_case   							=						{
    '''bert-base-uncased''': '''https://huggingface.co/bert-base-uncased/resolve/main/config.json''',
    '''bert-large-uncased''': '''https://huggingface.co/bert-large-uncased/resolve/main/config.json''',
    '''bert-base-cased''': '''https://huggingface.co/bert-base-cased/resolve/main/config.json''',
    '''bert-large-cased''': '''https://huggingface.co/bert-large-cased/resolve/main/config.json''',
    '''bert-base-multilingual-uncased''': '''https://huggingface.co/bert-base-multilingual-uncased/resolve/main/config.json''',
    '''bert-base-multilingual-cased''': '''https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json''',
    '''bert-base-chinese''': '''https://huggingface.co/bert-base-chinese/resolve/main/config.json''',
    '''bert-base-german-cased''': '''https://huggingface.co/bert-base-german-cased/resolve/main/config.json''',
    '''bert-large-uncased-whole-word-masking''': (
        '''https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/config.json'''
    ),
    '''bert-large-cased-whole-word-masking''': (
        '''https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/config.json'''
    ),
    '''bert-large-uncased-whole-word-masking-finetuned-squad''': (
        '''https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/config.json'''
    ),
    '''bert-large-cased-whole-word-masking-finetuned-squad''': (
        '''https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/config.json'''
    ),
    '''bert-base-cased-finetuned-mrpc''': '''https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/config.json''',
    '''bert-base-german-dbmdz-cased''': '''https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/config.json''',
    '''bert-base-german-dbmdz-uncased''': '''https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/config.json''',
    '''cl-tohoku/bert-base-japanese''': '''https://huggingface.co/cl-tohoku/bert-base-japanese/resolve/main/config.json''',
    '''cl-tohoku/bert-base-japanese-whole-word-masking''': (
        '''https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking/resolve/main/config.json'''
    ),
    '''cl-tohoku/bert-base-japanese-char''': (
        '''https://huggingface.co/cl-tohoku/bert-base-japanese-char/resolve/main/config.json'''
    ),
    '''cl-tohoku/bert-base-japanese-char-whole-word-masking''': (
        '''https://huggingface.co/cl-tohoku/bert-base-japanese-char-whole-word-masking/resolve/main/config.json'''
    ),
    '''TurkuNLP/bert-base-finnish-cased-v1''': (
        '''https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/config.json'''
    ),
    '''TurkuNLP/bert-base-finnish-uncased-v1''': (
        '''https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/config.json'''
    ),
    '''wietsedv/bert-base-dutch-cased''': '''https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/config.json''',
    # See all BERT models at https://huggingface.co/models?filter=bert
}



class 	__lowerCamelCase			(_a						):
       _lowercase											=     """bert"""







       def __init__(			self: Any,A_: Dict=3_0522,A_: Optional[Any]=768,A_: Union[str, Any]=12,A_: List[Any]=12,A_: Optional[int]=3072,A_: Union[str, Any]="gelu",A_: List[str]=0.1,A_: Dict=0.1,A_: Optional[int]=512,A_: Optional[Any]=2,A_: Union[str, Any]=0.0_2,A_: List[Any]=1E-12,A_: Optional[int]=0,A_: List[Any]="absolute",A_: str=True,A_: Union[str, Any]=None,**A_: int,):






            '''simple docstring'''




            super().__init__(pad_token_id=A_,**A_					)

            __UpperCamelCase =			vocab_size
            __UpperCamelCase =			hidden_size
            __UpperCamelCase =			num_hidden_layers
            __UpperCamelCase =			num_attention_heads
            __UpperCamelCase =			hidden_act
            __UpperCamelCase =			intermediate_size
            __UpperCamelCase =			hidden_dropout_prob
            __UpperCamelCase =			attention_probs_dropout_prob
            __UpperCamelCase =			max_position_embeddings
            __UpperCamelCase =			type_vocab_size
            __UpperCamelCase =			initializer_range
            __UpperCamelCase =			layer_norm_eps
            __UpperCamelCase =			position_embedding_type
            __UpperCamelCase =			use_cache
            __UpperCamelCase =			classifier_dropout



class 	__lowerCamelCase			(_a						):







       @property
       def 		snake_case_	(			self: Optional[int]					):






            '''simple docstring'''




            if self.task == "multiple-choice":
                 __UpperCamelCase =			{0: 'batch', 1: 'choice', 2: 'sequence'}
            else:
                 __UpperCamelCase =			{0: 'batch', 1: 'sequence'}
            return OrderedDict(
                [
                    ('input_ids', dynamic_axis),
                    ('attention_mask', dynamic_axis),
                    ('token_type_ids', dynamic_axis),
                ]					)


