



"""simple docstring"""






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

import cva
__snake_case							:   Optional[Any]      =    ''
__snake_case							:   List[str]      =    ''
__snake_case							:   Dict      =    ''
__snake_case							:   List[str]      =    1  # (0 is vertical, 1 is horizontal)


def 			_lowercase				(  )						->   None:
			__lowerCAmelCase						,	__lowerCAmelCase      :  Union[str, Any]												=       get_dataset(__snake_case					,__snake_case	)
			print("Processing..."	)
			__lowerCAmelCase						,	__lowerCAmelCase						,	__lowerCAmelCase      :  Optional[Any]												=       update_image_and_anno(__snake_case					,__snake_case					,__snake_case	)

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


def 			_lowercase				(  __snake_case					,__snake_case	)						->   tuple[list, list]:
			__lowerCAmelCase      :  List[Any]												=       []
			__lowerCAmelCase      :  List[str]												=       []
			for label_file in glob.glob(os.path.join(__snake_case					,"*.txt"	)	):
						__lowerCAmelCase      :  Optional[int]												=       label_file.split(os.sep	)[-1].rsplit("."					,1	)[0]
						with open(__snake_case	) as in_file:
									__lowerCAmelCase      :  Any												=       in_file.readlines()
						__lowerCAmelCase      :  Optional[Any]												=       os.path.join(__snake_case					,F"""{label_name}.jpg"""	)

						__lowerCAmelCase      :  Optional[int]												=       []
						for obj_list in obj_lists:
									__lowerCAmelCase      :  List[Any]												=       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(__snake_case	)
						labels.append(__snake_case	)
			return img_paths, labels


def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case = 1	)						->   tuple[list, list, list]:
			__lowerCAmelCase      :  Tuple												=       []
			__lowerCAmelCase      :  Union[str, Any]												=       []
			__lowerCAmelCase      :  List[str]												=       []
			for idx in range(len(__snake_case	)	):
						__lowerCAmelCase      :  Tuple												=       []
						__lowerCAmelCase      :  int												=       img_list[idx]
						path_list.append(__snake_case	)
						__lowerCAmelCase      :  Union[str, Any]												=       anno_list[idx]
						__lowerCAmelCase      :  List[str]												=       cva.imread(__snake_case	)
						if flip_type == 1:
									__lowerCAmelCase      :  str												=       cva.flip(__snake_case					,__snake_case	)
									for bbox in img_annos:
												__lowerCAmelCase      :  List[str]												=       1 - bbox[1]
												new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]	)
						elif flip_type == 0:
									__lowerCAmelCase      :  str												=       cva.flip(__snake_case					,__snake_case	)
									for bbox in img_annos:
												__lowerCAmelCase      :  Any												=       1 - bbox[2]
												new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]	)
						new_annos_lists.append(__snake_case	)
						new_imgs_list.append(__snake_case	)
			return new_imgs_list, new_annos_lists, path_list


def 			_lowercase				(  __snake_case = 32	)						->   str:
			assert number_char > 1, "The number of character should greater than 1"
			__lowerCAmelCase      :  Union[str, Any]												=       ascii_lowercase + digits
			return "".join(random.choice(__snake_case	) for _ in range(__snake_case	)	)


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




"""simple docstring"""






import os
import unittest

from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 			A__   (  __SCREAMING_SNAKE_CASE  ,		unittest.TestCase							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE          =	FunnelTokenizer
	SCREAMING_SNAKE_CASE          =	FunnelTokenizerFast
	SCREAMING_SNAKE_CASE          =	True
	SCREAMING_SNAKE_CASE          =	True

	def 							_SCREAMING_SNAKE_CASE   (     self:		Tuple)				->       Optional[int]:

				"""simple docstring"""

				super().setUp()

				__lowerCAmelCase      :  str												=       [
				    "<unk>",
				    "<cls>",
				    "<sep>",
				    "want",
				    "##want",
				    "##ed",
				    "wa",
				    "un",
				    "runn",
				    "##ing",
				    ",",
				    "low",
				    "lowest",
				]
				__lowerCAmelCase      :  int												=       os.path.join(self.tmpdirname       ,			VOCAB_FILES_NAMES["vocab_file"])
				with open(self.vocab_file       ,			"w"       ,			encoding="utf-8") as vocab_writer:
							vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))

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

				"""simple docstring"""

				return FunnelTokenizer.from_pretrained(self.tmpdirname       ,			**_SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE   (     self:		Any       ,			**_SCREAMING_SNAKE_CASE:		Any)				->       str:

				"""simple docstring"""

				return FunnelTokenizerFast.from_pretrained(self.tmpdirname       ,			**_SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE   (     self:		Tuple       ,			_SCREAMING_SNAKE_CASE:		str)				->       Any:

				"""simple docstring"""

				__lowerCAmelCase      :  Union[str, Any]												=       "UNwant\u00E9d,running"
				__lowerCAmelCase      :  str												=       "unwanted, running"
				return input_text, output_text

	def 							_SCREAMING_SNAKE_CASE   (     self:		Optional[int])				->       List[str]:

				"""simple docstring"""

				__lowerCAmelCase      :  Any												=       self.tokenizer_class(self.vocab_file)

				__lowerCAmelCase      :  Any												=       tokenizer.tokenize("UNwant\u00E9d,running")
				self.assertListEqual(_SCREAMING_SNAKE_CASE       ,			["un", "##want", "##ed", ",", "runn", "##ing"])
				self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE)       ,			[7, 4, 5, 10, 8, 9])







	def 							_SCREAMING_SNAKE_CASE   (     self:		List[str])				->       List[str]:

				"""simple docstring"""

				__lowerCAmelCase      :  Optional[Any]												=       self.get_tokenizers(do_lower_case=_SCREAMING_SNAKE_CASE)
				for tokenizer in tokenizers:
							__lowerCAmelCase      :  List[str]												=       tokenizer("UNwant\u00E9d,running")
							__lowerCAmelCase      :  Optional[int]												=       len(inputs["input_ids"]) - 1
							self.assertListEqual(inputs["token_type_ids"]       ,			[2] + [0] * sentence_len)

							__lowerCAmelCase      :  List[str]												=       tokenizer("UNwant\u00E9d,running"       ,			"UNwant\u00E9d,running")
							self.assertListEqual(inputs["token_type_ids"]       ,			[2] + [0] * sentence_len + [1] * sentence_len)