



'''simple docstring'''

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

import cva
import numpy as np

# Parrameters
a							   =				(720, 1_280)  # Height, Width
a							   =				(0.4, 0.6)  # if height or width lower than this scale, drop it.
a							   =				1 / 100
a							   =				''
a							   =				''
a							   =				''
a							   =				250







def a_     (    )				->					None:





			"""simple docstring"""







			snake_case							,  snake_case:    Optional[Any]      							=get_dataset(__UpperCAmelCase				,							__UpperCAmelCase					)
			for index in range(__UpperCAmelCase					):
						snake_case:    Tuple      							=random.sample(range(len(__UpperCAmelCase					)					)				,							4					)
						snake_case							,  snake_case							,  snake_case:    List[Any]      							=update_image_and_anno(
						    __UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase				,							filter_scale=__UpperCAmelCase				,							)

						# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
						snake_case:    Union[str, Any]      							=random_chars(32					)
						snake_case:    str      							=path.split(os.sep					)[-1].rsplit('.'				,							1					)[0]
						snake_case:    Union[str, Any]      							=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:    Optional[Any]      							=[]
						for anno in new_annos:
									snake_case:    str      							=anno[3] - anno[1]
									snake_case:    List[str]      							=anno[4] - anno[2]
									snake_case:    Optional[Any]      							=anno[1] + width / 2
									snake_case:    Optional[Any]      							=anno[2] + height / 2
									snake_case:    Tuple      							=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 a_     (    __UpperCAmelCase				,							__UpperCAmelCase					)				->					tuple[list, list]:





			"""simple docstring"""







			snake_case:    int      							=[]
			snake_case:    Union[str, Any]      							=[]
			for label_file in glob.glob(os.path.join(__UpperCAmelCase				,							'*.txt'					)					):
						snake_case:    Tuple      							=label_file.split(os.sep					)[-1].rsplit('.'				,							1					)[0]
						with open(__UpperCAmelCase					) as in_file:
									snake_case:    Union[str, Any]      							=in_file.readlines()
						snake_case:    Optional[Any]      							=os.path.join(__UpperCAmelCase				,							f'''{label_name}.jpg'''					)

						snake_case:    List[Any]      							=[]
						for obj_list in obj_lists:
									snake_case:    Optional[int]      							=obj_list.rstrip('\n'					).split(' '					)
									snake_case:    Tuple      							=float(obj[1]					) - float(obj[3]					) / 2
									snake_case:    List[str]      							=float(obj[2]					) - float(obj[4]					) / 2
									snake_case:    Union[str, Any]      							=float(obj[1]					) + float(obj[3]					) / 2
									snake_case:    Dict      							=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 a_     (    __UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase = 0.0				,							)				->					tuple[list, list, str]:





			"""simple docstring"""







			snake_case:    Optional[Any]      							=np.zeros([output_size[0], output_size[1], 3]				,							dtype=np.uinta					)
			snake_case:    Dict      							=scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
			snake_case:    int      							=scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
			snake_case:    List[str]      							=int(scale_x * output_size[1]					)
			snake_case:    Tuple      							=int(scale_y * output_size[0]					)

			snake_case:    Optional[int]      							=[]
			snake_case:    List[Any]      							=[]
			for i, index in enumerate(__UpperCAmelCase					):
						snake_case:    List[Any]      							=all_img_list[index]
						path_list.append(__UpperCAmelCase					)
						snake_case:    Union[str, Any]      							=all_annos[index]
						snake_case:    Optional[int]      							=cva.imread(__UpperCAmelCase					)
						if i == 0:  # top-left
									snake_case:    int      							=cva.resize(__UpperCAmelCase				,							(divid_point_x, divid_point_y)					)
									snake_case:    Optional[int]      							=img
									for bbox in img_annos:
												snake_case:    List[Any]      							=bbox[1] * scale_x
												snake_case:    Union[str, Any]      							=bbox[2] * scale_y
												snake_case:    Dict      							=bbox[3] * scale_x
												snake_case:    List[Any]      							=bbox[4] * scale_y
												new_anno.append([bbox[0], xmin, ymin, xmax, ymax]					)
						elif i == 1:  # top-right
									snake_case:    List[Any]      							=cva.resize(__UpperCAmelCase				,							(output_size[1] - divid_point_x, divid_point_y)					)
									snake_case:    Optional[int]      							=img
									for bbox in img_annos:
												snake_case:    Optional[int]      							=scale_x + bbox[1] * (1 - scale_x)
												snake_case:    Tuple      							=bbox[2] * scale_y
												snake_case:    int      							=scale_x + bbox[3] * (1 - scale_x)
												snake_case:    int      							=bbox[4] * scale_y
												new_anno.append([bbox[0], xmin, ymin, xmax, ymax]					)
						elif i == 2:  # bottom-left
									snake_case:    Optional[Any]      							=cva.resize(__UpperCAmelCase				,							(divid_point_x, output_size[0] - divid_point_y)					)
									snake_case:    Optional[Any]      							=img
									for bbox in img_annos:
												snake_case:    Optional[Any]      							=bbox[1] * scale_x
												snake_case:    str      							=scale_y + bbox[2] * (1 - scale_y)
												snake_case:    Union[str, Any]      							=bbox[3] * scale_x
												snake_case:    Optional[int]      							=scale_y + bbox[4] * (1 - scale_y)
												new_anno.append([bbox[0], xmin, ymin, xmax, ymax]					)
						else:  # bottom-right
									snake_case:    int      							=cva.resize(
									    __UpperCAmelCase				,							(output_size[1] - divid_point_x, output_size[0] - divid_point_y)					)
									snake_case:    int      							=img
									for bbox in img_annos:
												snake_case:    List[str]      							=scale_x + bbox[1] * (1 - scale_x)
												snake_case:    int      							=scale_y + bbox[2] * (1 - scale_y)
												snake_case:    Union[str, Any]      							=scale_x + bbox[3] * (1 - scale_x)
												snake_case:    Dict      							=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:    Dict      							=[
						    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 a_     (    __UpperCAmelCase					)				->					str:





			"""simple docstring"""







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


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









'''simple docstring'''

import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 						a_		(     snake_case    ,   unittest.TestCase    ):
							UpperCAmelCase			:		int        =				MgpstrTokenizer
							UpperCAmelCase			:		List[Any]        =				False
							UpperCAmelCase			:		Optional[int]        =				{}
							UpperCAmelCase			:		Any        =				False


							def    UpperCamelCase     (				self   :						Any			)			->					Dict:
										super().setUp()

										# fmt: off
										snake_case:    List[Any]      							=['[GO]', '[s]', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']
										# fmt: on
										snake_case:    Union[str, Any]      							=dict(zip(a_      ,						range(len(a_			)			)			)			)

										snake_case:    List[Any]      							=os.path.join(self.tmpdirname      ,						VOCAB_FILES_NAMES['vocab_file']			)
										with open(self.vocab_file      ,						'w'      ,						encoding='utf-8'			) as fp:
													fp.write(json.dumps(a_			) + '\n'			)


							def    UpperCamelCase     (				self   :						Optional[Any]      ,						**a_   :						List[Any]			)			->					str:
										return MgpstrTokenizer.from_pretrained(self.tmpdirname      ,						**a_			)


							def    UpperCamelCase     (				self   :						int      ,						a_   :						Dict			)			->					int:
										snake_case:    Any      							='tester'
										snake_case:    List[str]      							='tester'
										return input_text, output_text


							@unittest.skip('MGP-STR always lower cases letters.'			)
							def    UpperCamelCase     (				self   :						Any			)			->					Dict:
										pass


							def    UpperCamelCase     (				self   :						Optional[int]			)			->					int:
										snake_case:    int      							=self.get_tokenizers(do_lower_case=a_			)
										for tokenizer in tokenizers:
													with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
																snake_case:    Optional[Any]      							='[SPECIAL_TOKEN]'

																tokenizer.add_special_tokens({'cls_token': special_token}			)
																snake_case:    List[str]      							=tokenizer.encode([special_token]      ,						add_special_tokens=a_			)
																self.assertEqual(len(a_			)      ,						1			)

																snake_case:    Union[str, Any]      							=tokenizer.decode(a_      ,						skip_special_tokens=a_			)
																self.assertTrue(special_token not in decoded			)


							def    UpperCamelCase     (				self   :						int			)			->					str:
										snake_case:    int      							=self.get_tokenizers()
										for tokenizer in tokenizers:
													with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
																snake_case							,  snake_case:    Dict      							=self.get_input_output_texts(a_			)

																snake_case:    Dict      							=tokenizer.tokenize(a_			)
																snake_case:    str      							=tokenizer.convert_tokens_to_ids(a_			)
																snake_case:    List[Any]      							=tokenizer.encode(a_      ,						add_special_tokens=a_			)
																self.assertListEqual(a_      ,						a_			)

																snake_case:    str      							=tokenizer.convert_ids_to_tokens(a_			)
																self.assertNotEqual(len(a_			)      ,						0			)
																snake_case:    Tuple      							=tokenizer.decode(a_			)
																self.assertIsInstance(a_      ,						a_			)

																self.assertEqual(text_a.replace(' '      ,						''			)      ,						a_			)


							@unittest.skip('MGP-STR tokenizer only handles one sequence.'			)
							def    UpperCamelCase     (				self   :						Dict			)			->					str:
										pass




							@unittest.skip('inputs cannot be pretokenized in MgpstrTokenizer'			)
							def    UpperCamelCase     (				self   :						Optional[Any]			)			->					Optional[int]:
										pass




