
'''simple docstring'''







from typing import Dict, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_pytesseract_available, is_vision_available, logging, requires_backends


if is_vision_available():
					import PIL

# soft dependency
if is_pytesseract_available():
					import pytesseract

lowercase    :							Dict      =					logging.get_logger(__name__)







def 				SCREAMING_SNAKE_CASE__	(   __A			,				__A			,				__A	)       ->	Union[str, Any]:
	return [
	    int(1_000 * (box[0] / width)	),
	    int(1_000 * (box[1] / height)	),
	    int(1_000 * (box[2] / width)	),
	    int(1_000 * (box[3] / height)	),
	]







def 				SCREAMING_SNAKE_CASE__	(   __A			,				__A			,				__A = None	)       ->	Any:
	_snake_case   						=		tesseract_config if tesseract_config is not None else ''

	# apply OCR
	_snake_case   						=		to_pil_image(__A	)
	_snake_case						, _snake_case   						=		pil_image.size
	_snake_case   						=		pytesseract.image_to_data(__A			,				lang=__A			,				output_type='dict'			,				config=__A	)
	_snake_case						, _snake_case						, _snake_case						, _snake_case						, _snake_case   						=		data['text'], data['left'], data['top'], data['width'], data['height']

	# filter empty words and corresponding coordinates
	_snake_case   						=		[idx for idx, word in enumerate(__A	) if not word.strip()]
	_snake_case   						=		[word for idx, word in enumerate(__A	) if idx not in irrelevant_indices]
	_snake_case   						=		[coord for idx, coord in enumerate(__A	) if idx not in irrelevant_indices]
	_snake_case   						=		[coord for idx, coord in enumerate(__A	) if idx not in irrelevant_indices]
	_snake_case   						=		[coord for idx, coord in enumerate(__A	) if idx not in irrelevant_indices]
	_snake_case   						=		[coord for idx, coord in enumerate(__A	) if idx not in irrelevant_indices]

	# turn coordinates into (left, top, left+width, top+height) format
	_snake_case   						=		[]
	for x, y, w, h in zip(__A			,				__A			,				__A			,				__A	):
		_snake_case   						=		[x, y, x + w, y + h]
		actual_boxes.append(__A	)

	# finally, normalize the bounding boxes
	_snake_case   						=		[]
	for box in actual_boxes:
		normalized_boxes.append(normalize_box(__A			,				__A			,				__A	)	)

	assert len(__A	) == len(__A	), "Not as many words as there are bounding boxes"

	return words, normalized_boxes





class 						__UpperCAmelCase      (					_lowerCamelCase						):
							__lowercase      		=       ["""pixel_values"""]


							def __init__(       self    ,   lowerCAmelCase_ = True    ,   lowerCAmelCase_ = None    ,   lowerCAmelCase_ = PILImageResampling.BILINEAR    ,   lowerCAmelCase_ = True    ,   lowerCAmelCase_ = None    ,   lowerCAmelCase_ = ""    ,   **lowerCAmelCase_    ,   ):





								"""simple docstring"""






								super().__init__(**lowerCAmelCase_  )
								_snake_case   						=		size if size is not None else {'height': 2_24, 'width': 2_24}
								_snake_case   						=		get_size_dict(lowerCAmelCase_  )

								_snake_case   						=		do_resize
								_snake_case   						=		size
								_snake_case   						=		resample
								_snake_case   						=		apply_ocr
								_snake_case   						=		ocr_lang
								_snake_case   						=		tesseract_config


							def  lowerCamelCase				(       self    ,   lowerCAmelCase_    ,   lowerCAmelCase_    ,   lowerCAmelCase_ = PILImageResampling.BILINEAR    ,   lowerCAmelCase_ = None    ,   **lowerCAmelCase_    ,   ):





								"""simple docstring"""






								_snake_case   						=		get_size_dict(lowerCAmelCase_  )
								if "height" not in size or "width" not in size:
									raise ValueError(F'The size dictionary must contain the keys \'height\' and \'width\'. Got {size.keys()}'  )
								_snake_case   						=		(size['height'], size['width'])
								return resize(lowerCAmelCase_    ,   size=lowerCAmelCase_    ,   resample=lowerCAmelCase_    ,   data_format=lowerCAmelCase_    ,   **lowerCAmelCase_  )




							def  lowerCamelCase				(       self    ,   lowerCAmelCase_    ,   lowerCAmelCase_ = None    ,   lowerCAmelCase_ = None    ,   lowerCAmelCase_ = None    ,   lowerCAmelCase_ = None    ,   lowerCAmelCase_ = None    ,   lowerCAmelCase_ = None    ,   lowerCAmelCase_ = None    ,   lowerCAmelCase_ = ChannelDimension.FIRST    ,   **lowerCAmelCase_    ,   ):





								"""simple docstring"""






								_snake_case   						=		do_resize if do_resize is not None else self.do_resize
								_snake_case   						=		size if size is not None else self.size
								_snake_case   						=		get_size_dict(lowerCAmelCase_  )
								_snake_case   						=		resample if resample is not None else self.resample
								_snake_case   						=		apply_ocr if apply_ocr is not None else self.apply_ocr
								_snake_case   						=		ocr_lang if ocr_lang is not None else self.ocr_lang
								_snake_case   						=		tesseract_config if tesseract_config is not None else self.tesseract_config

								_snake_case   						=		make_list_of_images(lowerCAmelCase_  )

								if not valid_images(lowerCAmelCase_  ):
									raise ValueError(
									    'Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, '
									    'torch.Tensor, tf.Tensor or jax.ndarray.'  )

								if do_resize and size is None:
									raise ValueError('Size must be specified if do_resize is True.'  )

								# All transformations expect numpy arrays.
								_snake_case   						=		[to_numpy_array(lowerCAmelCase_  ) for image in images]

								if apply_ocr:
									requires_backends(self    ,   'pytesseract'  )
									_snake_case   						=		[]
									_snake_case   						=		[]
									for image in images:
										_snake_case						, _snake_case   						=		apply_tesseract(lowerCAmelCase_    ,   lowerCAmelCase_    ,   lowerCAmelCase_  )
										words_batch.append(lowerCAmelCase_  )
										boxes_batch.append(lowerCAmelCase_  )

								if do_resize:
									_snake_case   						=		[self.resize(image=lowerCAmelCase_    ,   size=lowerCAmelCase_    ,   resample=lowerCAmelCase_  ) for image in images]

								# flip color channels from RGB to BGR (as Detectron2 requires this)
								_snake_case   						=		[flip_channel_order(lowerCAmelCase_  ) for image in images]
								_snake_case   						=		[to_channel_dimension_format(lowerCAmelCase_    ,   lowerCAmelCase_  ) for image in images]

								_snake_case   						=		BatchFeature(data={'pixel_values': images}    ,   tensor_type=lowerCAmelCase_  )

								if apply_ocr:
									_snake_case   						=		words_batch
									_snake_case   						=		boxes_batch
								return data









"""simple docstring"""



import argparse
import os
import re

import packaging.version


__A		:       List[str]  				=		'''examples/'''
__A		:       int  				=		{
    '''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
    '''init''': (re.compile(R'''^__version__\s+=\s+"([^"]+)"\s*$''', re.MULTILINE), '''__version__ = "VERSION"\n'''),
    '''setup''': (re.compile(R'''^(\s*)version\s*=\s*"[^"]+",''', re.MULTILINE), R'''\1version="VERSION",'''),
    '''doc''': (re.compile(R'''^(\s*)release\s*=\s*"[^"]+"$''', re.MULTILINE), '''release = "VERSION"\n'''),
}
__A		:       Dict  				=		{
    '''init''': '''src/transformers/__init__.py''',
    '''setup''': '''setup.py''',
}
__A		:       Optional[int]  				=		'''README.md'''



def 						lowercase    (				__snake_case				: int		,					__snake_case				: Any		,					__snake_case				: int	):
		with open(__snake_case		,					'''r'''		,					encoding='''utf-8'''		,					newline='''\n'''	) as f:
				lowercase_ : int							       =   f.read()
		lowercase_       ,					lowercase_ : List[str]							       =   REPLACE_PATTERNS[pattern]
		lowercase_ : Union[str, Any]							       =   replace.replace('''VERSION'''		,					__snake_case	)
		lowercase_ : Optional[Any]							       =   re_pattern.sub(__snake_case		,					__snake_case	)
		with open(__snake_case		,					'''w'''		,					encoding='''utf-8'''		,					newline='''\n'''	) as f:
				f.write(__snake_case	)



def 						lowercase    (				__snake_case				: int	):
		for folder, directories, fnames in os.walk(__snake_case	):
				# Removing some of the folders with non-actively maintained examples from the walk
				if "research_projects" in directories:
						directories.remove('''research_projects'''	)
				if "legacy" in directories:
						directories.remove('''legacy'''	)
				for fname in fnames:
						if fname.endswith('''.py'''	):
								update_version_in_file(os.path.join(__snake_case		,					__snake_case	)		,					__snake_case		,					pattern='''examples'''	)



def 						lowercase    (				__snake_case				: Optional[Any]		,					__snake_case				: Optional[Any]=False	):
		for pattern, fname in REPLACE_FILES.items():
				update_version_in_file(__snake_case		,					__snake_case		,					__snake_case	)
		if not patch:
				update_version_in_examples(__snake_case	)



def 						lowercase    (				):
		lowercase_ : Union[str, Any]							       =   '''🤗 Transformers currently provides the following architectures'''
		lowercase_ : Union[str, Any]							       =   '''1. Want to contribute a new model?'''
		with open(__snake_case		,					'''r'''		,					encoding='''utf-8'''		,					newline='''\n'''	) as f:
				lowercase_ : List[str]							       =   f.readlines()

		# Find the start of the list.
		lowercase_ : Optional[Any]							       =   0
		while not lines[start_index].startswith(_start_prompt	):
				start_index += 1
		start_index += 1

		lowercase_ : str							       =   start_index
		# Update the lines in the model list.
		while not lines[index].startswith(_end_prompt	):
				if lines[index].startswith('''1.'''	):
						lowercase_ : str							       =   lines[index].replace(
						    '''https://huggingface.co/docs/transformers/main/model_doc'''		,					'''https://huggingface.co/docs/transformers/model_doc'''		,					)
				index += 1

		with open(__snake_case		,					'''w'''		,					encoding='''utf-8'''		,					newline='''\n'''	) as f:
				f.writelines(__snake_case	)



def 						lowercase    (				):
		with open(REPLACE_FILES['''init''']		,					'''r'''	) as f:
				lowercase_ : List[Any]							       =   f.read()
		lowercase_ : List[str]							       =   REPLACE_PATTERNS['''init'''][0].search(__snake_case	).groups()[0]
		return packaging.version.parse(__snake_case	)



def 						lowercase    (				__snake_case				: Optional[Any]=False	):
		lowercase_ : str							       =   get_version()
		if patch and default_version.is_devrelease:
				raise ValueError('''Can\'t create a patch version from the dev branch, checkout a released version!'''	)
		if default_version.is_devrelease:
				lowercase_ : Optional[Any]							       =   default_version.base_version
		elif patch:
				lowercase_ : Optional[int]							       =   F'''{default_version.major}.{default_version.minor}.{default_version.micro + 1}'''
		else:
				lowercase_ : Optional[int]							       =   F'''{default_version.major}.{default_version.minor + 1}.0'''

		# Now let's ask nicely if that's the right one.
		lowercase_ : int							       =   input(F'''Which version are you releasing? [{default_version}]'''	)
		if len(__snake_case	) == 0:
				lowercase_ : Dict							       =   default_version

		print(F'''Updating version to {version}.'''	)
		global_version_update(__snake_case		,					patch=__snake_case	)
		if not patch:
				print('''Cleaning main README, don\'t forget to run `make fix-copies`.'''	)
				clean_main_ref_in_model_list()



def 						lowercase    (				):
		lowercase_ : List[Any]							       =   get_version()
		lowercase_ : List[str]							       =   F'''{current_version.major}.{current_version.minor + 1}.0.dev0'''
		lowercase_ : Any							       =   current_version.base_version

		# Check with the user we got that right.
		lowercase_ : Tuple							       =   input(F'''Which version are we developing now? [{dev_version}]'''	)
		if len(__snake_case	) == 0:
				lowercase_ : str							       =   dev_version

		print(F'''Updating version to {version}.'''	)
		global_version_update(__snake_case	)
		print('''Cleaning main README, don\'t forget to run `make fix-copies`.'''	)
		clean_main_ref_in_model_list()


if __name__ == "__main__":
						__A		:       int  				=		argparse.ArgumentParser()
						parser.add_argument('''--post_release''', action='''store_true''', help='''Whether this is pre or post release.''')
						parser.add_argument('''--patch''', action='''store_true''', help='''Whether or not this is a patch release.''')
						__A		:       Any  				=		parser.parse_args()
						if not args.post_release:
												pre_release_work(patch=args.patch)
						elif args.patch:
												print('''Nothing to do after a patch :-)''')
						else:
												post_release_work()



