
'''simple docstring'''







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

import cva
import numpy as np

# Parrameters
_lowercase			:  Optional[int]   							=	(7_2_0, 1_2_8_0)  # Height, Width
_lowercase			:  List[Any]   							=	(0.4, 0.6)  # if height or width lower than this scale, drop it.
_lowercase			:  Optional[int]   							=	1 / 1_0_0
_lowercase			:  Any   							=	""
_lowercase			:  Union[str, Any]   							=	""
_lowercase			:  Optional[int]   							=	""
_lowercase			:  Union[str, Any]   							=	2_5_0
def  snake_case_		(    ):



						"""simple docstring"""





						lowercase_						,			lowercase_     :					int													=	get_dataset(__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE							)
						for index in range(__SCREAMING_SNAKE_CASE							):
												lowercase_     :					str													=	random.sample(range(len(__SCREAMING_SNAKE_CASE							)							)				,				4							)
												lowercase_						,			lowercase_						,			lowercase_     :					List[Any]													=	update_image_and_anno(
												    __SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE				,				filter_scale=__SCREAMING_SNAKE_CASE				,				)

												# Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
												lowercase_     :					int													=	random_chars(32							)
												lowercase_     :					int													=	path.split(os.sep							)[-1].rsplit('''.'''				,				1							)[0]
												lowercase_     :					Tuple													=	F'''{OUTPUT_DIR}/{file_name}_MOSAIC_{letter_code}'''
												cva.imwrite(F'''{file_root}.jpg'''				,				__SCREAMING_SNAKE_CASE				,				[cva.IMWRITE_JPEG_QUALITY, 85]							)
												print(F'''Succeeded {index+1}/{NUMBER_IMAGES} with {file_name}'''							)
												lowercase_     :					Any													=	[]
												for anno in new_annos:
																		lowercase_     :					Tuple													=	anno[3] - anno[1]
																		lowercase_     :					Dict													=	anno[4] - anno[2]
																		lowercase_     :					List[Any]													=	anno[1] + width / 2
																		lowercase_     :					List[Any]													=	anno[2] + height / 2
																		lowercase_     :					Dict													=	F'''{anno[0]} {x_center} {y_center} {width} {height}'''
																		annos_list.append(__SCREAMING_SNAKE_CASE							)
												with open(F'''{file_root}.txt'''				,				'''w'''							) as outfile:
																		outfile.write('''\n'''.join(line for line in annos_list							)							)
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			str				,				__SCREAMING_SNAKE_CASE :			str							):



						"""simple docstring"""





						lowercase_     :					str													=	[]
						lowercase_     :					Union[str, Any]													=	[]
						for label_file in glob.glob(os.path.join(__SCREAMING_SNAKE_CASE				,				'''*.txt'''							)							):
												lowercase_     :					Union[str, Any]													=	label_file.split(os.sep							)[-1].rsplit('''.'''				,				1							)[0]
												with open(__SCREAMING_SNAKE_CASE							) as in_file:
																		lowercase_     :					Union[str, Any]													=	in_file.readlines()
												lowercase_     :					Dict													=	os.path.join(__SCREAMING_SNAKE_CASE				,				F'''{label_name}.jpg'''							)

												lowercase_     :					List[Any]													=	[]
												for obj_list in obj_lists:
																		lowercase_     :					str													=	obj_list.rstrip('''\n'''							).split(''' '''							)
																		lowercase_     :					List[str]													=	float(obj[1]							) - float(obj[3]							) / 2
																		lowercase_     :					Union[str, Any]													=	float(obj[2]							) - float(obj[4]							) / 2
																		lowercase_     :					Optional[int]													=	float(obj[1]							) + float(obj[3]							) / 2
																		lowercase_     :					Any													=	float(obj[2]							) + float(obj[4]							) / 2

																		boxes.append([int(obj[0]							), xmin, ymin, xmax, ymax]							)
												if not boxes:
																		continue
												img_paths.append(__SCREAMING_SNAKE_CASE							)
												labels.append(__SCREAMING_SNAKE_CASE							)
						return img_paths, labels
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			list				,				__SCREAMING_SNAKE_CASE :			list				,				__SCREAMING_SNAKE_CASE :			list[int]				,				__SCREAMING_SNAKE_CASE :			tuple[int, int]				,				__SCREAMING_SNAKE_CASE :			tuple[float, float]				,				__SCREAMING_SNAKE_CASE :			float = 0.0				,				):



						"""simple docstring"""





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

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



						"""simple docstring"""





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


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





'''simple docstring'''







import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 			lowerCAmelCase__       (  lowerCamelCase_   ,						unittest.TestCase					):
					lowerCAmelCase_					       =					None
					lowerCAmelCase_					       =					BloomTokenizerFast
					lowerCAmelCase_					       =					BloomTokenizerFast
					lowerCAmelCase_					       =					True
					lowerCAmelCase_					       =					False
					lowerCAmelCase_					       =					'''tokenizer_file'''
					lowerCAmelCase_					       =					{'''bos_token''': '''<s>''', '''eos_token''': '''</s>''', '''unk_token''': '''<unk>''', '''pad_token''': '''<pad>'''}






					def      _snake_case   (       self		):


											"""simple docstring"""





											super().setUp()
											lowercase_     :					List[Any]													=	BloomTokenizerFast.from_pretrained('''bigscience/tokenizer'''		)
											tokenizer.save_pretrained(self.tmpdirname		)






					def      _snake_case   (       self    ,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											kwargs.update(self.special_tokens_map		)
											return BloomTokenizerFast.from_pretrained(self.tmpdirname    ,							**__SCREAMING_SNAKE_CASE		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					Tuple													=	self.get_rust_tokenizer()

											lowercase_     :					Optional[Any]													=	['''The quick brown fox</s>''', '''jumps over the lazy dog</s>''']
											lowercase_     :					Union[str, Any]													=	[[21_75, 2_37_14, 7_31_73, 14_42_52, 2], [77, 13_26_19, 34_78, 3_68, 10_95_86, 3_54_33, 2]]

											lowercase_     :					Dict													=	tokenizer.batch_encode_plus(__SCREAMING_SNAKE_CASE		)['''input_ids''']
											self.assertListEqual(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					Tuple													=	tokenizer.batch_decode(__SCREAMING_SNAKE_CASE		)
											self.assertListEqual(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE=6		):


											"""simple docstring"""





											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
																							lowercase_     :					int													=	self.rust_tokenizer_class.from_pretrained(__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE		)
																							# tokenizer_r.pad_token = None # Hotfixing padding = None
																							# Simple input
																							lowercase_     :					Optional[int]													=	'''This is a simple input'''
																							lowercase_     :					List[str]													=	['''This is a simple input 1''', '''This is a simple input 2''']
																							lowercase_     :					List[str]													=	('''This is a simple input''', '''This is a pair''')
																							lowercase_     :					Union[str, Any]													=	[
																							    ('''This is a simple input 1''', '''This is a simple input 2'''),
																							    ('''This is a simple pair 1''', '''This is a simple pair 2'''),
																							]

																							# Simple input tests
																							try:
																													tokenizer_r.encode(__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE		)
																													tokenizer_r.encode_plus(__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE		)

																													tokenizer_r.batch_encode_plus(__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE		)
																													tokenizer_r.encode(__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE		)
																													tokenizer_r.batch_encode_plus(__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE		)
																							except ValueError:
																													self.fail('''Bloom Tokenizer should be able to deal with padding'''		)

																							lowercase_     :					Optional[Any]													=	None  # Hotfixing padding = None
																							self.assertRaises(__SCREAMING_SNAKE_CASE    ,							tokenizer_r.encode    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''		)

																							# Simple input
																							self.assertRaises(__SCREAMING_SNAKE_CASE    ,							tokenizer_r.encode_plus    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''		)

																							# Simple input
																							self.assertRaises(
																							    __SCREAMING_SNAKE_CASE    ,							tokenizer_r.batch_encode_plus    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''    ,							)

																							# Pair input
																							self.assertRaises(__SCREAMING_SNAKE_CASE    ,							tokenizer_r.encode    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''		)

																							# Pair input
																							self.assertRaises(__SCREAMING_SNAKE_CASE    ,							tokenizer_r.encode_plus    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''		)

																							# Pair input
																							self.assertRaises(
																							    __SCREAMING_SNAKE_CASE    ,							tokenizer_r.batch_encode_plus    ,							__SCREAMING_SNAKE_CASE    ,							max_length=__SCREAMING_SNAKE_CASE    ,							padding='''max_length'''    ,							)






					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					List[str]													=	self.get_rust_tokenizer()
											lowercase_     :					Tuple													=	load_dataset('''xnli'''    ,							'''all_languages'''    ,							split='''test'''    ,							streaming=__SCREAMING_SNAKE_CASE		)

											lowercase_     :					Optional[int]													=	next(iter(__SCREAMING_SNAKE_CASE		)		)['''premise''']  # pick up one data
											lowercase_     :					List[Any]													=	list(sample_data.values()		)

											lowercase_     :					Tuple													=	list(map(tokenizer.encode    ,							__SCREAMING_SNAKE_CASE		)		)
											lowercase_     :					Any													=	[tokenizer.decode(__SCREAMING_SNAKE_CASE    ,							clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE		) for x in output_tokens]
											self.assertListEqual(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)






					def      _snake_case   (       self		):


											"""simple docstring"""





											self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map		)    ,							1		)
											self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()		)[0]		)    ,							1		)



