'''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

_A			:      str					      =				logging.get_logger(__name__)







def      UpperCamelCase_						(					snake_case_       :       List[Any]						,		snake_case_       :       Tuple						,		snake_case_       :       List[Any]      )					->     List[str]:






 '''simple docstring'''

 return [
     int(10_00 * (box[0] / width)      ),
     int(10_00 * (box[1] / height)      ),
     int(10_00 * (box[2] / width)      ),
     int(10_00 * (box[3] / height)      ),
 ]







def      UpperCamelCase_						(					snake_case_       :       np.ndarray						,		snake_case_       :       Optional[str]						,		snake_case_       :       Optional[str] = None      )					->     Optional[Any]:






 '''simple docstring'''

 __lowerCAmelCase											=						tesseract_config if tesseract_config is not None else ''''''

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

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

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

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

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

 return words, normalized_boxes







class 				_lowercase     (				A__			):


 '''simple docstring'''






 _SCREAMING_SNAKE_CASE     :       Tuple      	=					["""pixel_values"""]
 def __init__(      self   :	Optional[int]      ,       SCREAMING_SNAKE_CASE__   :	bool = True      ,       SCREAMING_SNAKE_CASE__   :	Dict[str, int] = None      ,       SCREAMING_SNAKE_CASE__   :	PILImageResampling = PILImageResampling.BILINEAR      ,       SCREAMING_SNAKE_CASE__   :	bool = True      ,       SCREAMING_SNAKE_CASE__   :	Optional[str] = None      ,       SCREAMING_SNAKE_CASE__   :	Optional[str] = ""      ,       **SCREAMING_SNAKE_CASE__   :	str      ,       )  ->    None:
  super().__init__(**__snake_case							)
  __lowerCAmelCase											=						size if size is not None else {'''height''': 2_24, '''width''': 2_24}
  __lowerCAmelCase											=						get_size_dict(__snake_case							)

  __lowerCAmelCase											=						do_resize
  __lowerCAmelCase											=						size
  __lowerCAmelCase											=						resample
  __lowerCAmelCase											=						apply_ocr
  __lowerCAmelCase											=						ocr_lang
  __lowerCAmelCase											=						tesseract_config
 def a					(      self   :	List[str]      ,       SCREAMING_SNAKE_CASE__   :	np.ndarray      ,       SCREAMING_SNAKE_CASE__   :	Dict[str, int]      ,       SCREAMING_SNAKE_CASE__   :	PILImageResampling = PILImageResampling.BILINEAR      ,       SCREAMING_SNAKE_CASE__   :	Optional[Union[str, ChannelDimension]] = None      ,       **SCREAMING_SNAKE_CASE__   :	List[str]      ,       )  ->    np.ndarray:
  __lowerCAmelCase											=						get_size_dict(__snake_case							)
  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()}"""							)
  __lowerCAmelCase											=						(size['''height'''], size['''width'''])
  return resize(__snake_case      ,       size=__snake_case      ,       resample=__snake_case      ,       data_format=__snake_case      ,       **__snake_case							)





 def a					(      self   :	Tuple      ,       SCREAMING_SNAKE_CASE__   :	ImageInput      ,       SCREAMING_SNAKE_CASE__   :	bool = None      ,       SCREAMING_SNAKE_CASE__   :	Dict[str, int] = None      ,       SCREAMING_SNAKE_CASE__   :	PILImageResampling = None      ,       SCREAMING_SNAKE_CASE__   :	bool = None      ,       SCREAMING_SNAKE_CASE__   :	Optional[str] = None      ,       SCREAMING_SNAKE_CASE__   :	Optional[str] = None      ,       SCREAMING_SNAKE_CASE__   :	Optional[Union[str, TensorType]] = None      ,       SCREAMING_SNAKE_CASE__   :	ChannelDimension = ChannelDimension.FIRST      ,       **SCREAMING_SNAKE_CASE__   :	List[Any]      ,       )  ->    PIL.Image.Image:
  __lowerCAmelCase											=						do_resize if do_resize is not None else self.do_resize
  __lowerCAmelCase											=						size if size is not None else self.size
  __lowerCAmelCase											=						get_size_dict(__snake_case							)
  __lowerCAmelCase											=						resample if resample is not None else self.resample
  __lowerCAmelCase											=						apply_ocr if apply_ocr is not None else self.apply_ocr
  __lowerCAmelCase											=						ocr_lang if ocr_lang is not None else self.ocr_lang
  __lowerCAmelCase											=						tesseract_config if tesseract_config is not None else self.tesseract_config

  __lowerCAmelCase											=						make_list_of_images(__snake_case							)

  if not valid_images(__snake_case							):
   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.
  __lowerCAmelCase											=						[to_numpy_array(__snake_case							) for image in images]

  if apply_ocr:
   requires_backends(self      ,       """pytesseract"""							)
   __lowerCAmelCase											=						[]
   __lowerCAmelCase											=						[]
   for image in images:
    __lowerCAmelCase											=						apply_tesseract(__snake_case      ,       __snake_case      ,       __snake_case							)
    words_batch.append(__snake_case							)
    boxes_batch.append(__snake_case							)

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

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

  __lowerCAmelCase											=						BatchFeature(data={"""pixel_values""": images}      ,       tensor_type=__snake_case							)

  if apply_ocr:
   __lowerCAmelCase											=						words_batch
   __lowerCAmelCase											=						boxes_batch
  return data











'''simple docstring'''






from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )  )      ->   IIRFilter:
							UpperCAmelCase :       Optional[int] 							=		tau * frequency / samplerate
							UpperCAmelCase :       List[Any] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Optional[Any] 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       int 							=		_sin / (2 * q_factor)

							UpperCAmelCase :       Any 							=		(1 - _cos) / 2
							UpperCAmelCase :       List[Any] 							=		1 - _cos

							UpperCAmelCase :       Union[str, Any] 							=		1 + alpha
							UpperCAmelCase :       Any 							=		-2 * _cos
							UpperCAmelCase :       Dict 							=		1 - alpha

							UpperCAmelCase :       Union[str, Any] 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )  )      ->   IIRFilter:
							UpperCAmelCase :       Any 							=		tau * frequency / samplerate
							UpperCAmelCase :       Tuple 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Tuple 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       Dict 							=		_sin / (2 * q_factor)

							UpperCAmelCase :       int 							=		(1 + _cos) / 2
							UpperCAmelCase :       List[Any] 							=		-1 - _cos

							UpperCAmelCase :       Tuple 							=		1 + alpha
							UpperCAmelCase :       List[str] 							=		-2 * _cos
							UpperCAmelCase :       Optional[Any] 							=		1 - alpha

							UpperCAmelCase :       Tuple 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )  )      ->   IIRFilter:
							UpperCAmelCase :       Optional[int] 							=		tau * frequency / samplerate
							UpperCAmelCase :       Optional[int] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Tuple 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       Optional[int] 							=		_sin / (2 * q_factor)

							UpperCAmelCase :       Union[str, Any] 							=		_sin / 2
							UpperCAmelCase :       Any 							=		0
							UpperCAmelCase :       int 							=		-ba

							UpperCAmelCase :       Optional[Any] 							=		1 + alpha
							UpperCAmelCase :       List[Any] 							=		-2 * _cos
							UpperCAmelCase :       Optional[Any] 							=		1 - alpha

							UpperCAmelCase :       int 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )  )      ->   IIRFilter:
							UpperCAmelCase :       List[str] 							=		tau * frequency / samplerate
							UpperCAmelCase :       Union[str, Any] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       str 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       Optional[Any] 							=		_sin / (2 * q_factor)

							UpperCAmelCase :       List[str] 							=		1 - alpha
							UpperCAmelCase :       Any 							=		-2 * _cos
							UpperCAmelCase :       Optional[int] 							=		1 + alpha

							UpperCAmelCase :       Union[str, Any] 							=		IIRFilter(2  )
							filt.set_coefficients([ba, ba, ba]   ,      [ba, ba, ba]  )
							return filt


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )   ,      )      ->   IIRFilter:
							UpperCAmelCase :       Optional[Any] 							=		tau * frequency / samplerate
							UpperCAmelCase :       Union[str, Any] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Optional[int] 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       Dict 							=		_sin / (2 * q_factor)
							UpperCAmelCase :       str 							=		10 ** (gain_db / 40)

							UpperCAmelCase :       int 							=		1 + alpha * big_a
							UpperCAmelCase :       Union[str, Any] 							=		-2 * _cos
							UpperCAmelCase :       Optional[Any] 							=		1 - alpha * big_a
							UpperCAmelCase :       Union[str, Any] 							=		1 + alpha / big_a
							UpperCAmelCase :       Tuple 							=		-2 * _cos
							UpperCAmelCase :       Any 							=		1 - alpha / big_a

							UpperCAmelCase :       Optional[Any] 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )   ,      )      ->   IIRFilter:
							UpperCAmelCase :       Any 							=		tau * frequency / samplerate
							UpperCAmelCase :       Optional[int] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Union[str, Any] 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       str 							=		_sin / (2 * q_factor)
							UpperCAmelCase :       List[str] 							=		10 ** (gain_db / 40)
							UpperCAmelCase :       Optional[int] 							=		(big_a + 1) - (big_a - 1) * _cos
							UpperCAmelCase :       int 							=		(big_a + 1) + (big_a - 1) * _cos
							UpperCAmelCase :       int 							=		(big_a - 1) - (big_a + 1) * _cos
							UpperCAmelCase :       Optional[int] 							=		(big_a - 1) + (big_a + 1) * _cos
							UpperCAmelCase :       str 							=		2 * sqrt(_lowerCAmelCase  ) * alpha

							UpperCAmelCase :       Dict 							=		big_a * (pmc + aaa)
							UpperCAmelCase :       Any 							=		2 * big_a * mpc
							UpperCAmelCase :       Union[str, Any] 							=		big_a * (pmc - aaa)
							UpperCAmelCase :       Optional[int] 							=		ppmc + aaa
							UpperCAmelCase :       Optional[Any] 							=		-2 * pmpc
							UpperCAmelCase :       Optional[Any] 							=		ppmc - aaa

							UpperCAmelCase :       int 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt




def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )   ,      )      ->   IIRFilter:
							UpperCAmelCase :       int 							=		tau * frequency / samplerate
							UpperCAmelCase :       Union[str, Any] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Union[str, Any] 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       Any 							=		_sin / (2 * q_factor)
							UpperCAmelCase :       int 							=		10 ** (gain_db / 40)
							UpperCAmelCase :       List[str] 							=		(big_a + 1) - (big_a - 1) * _cos
							UpperCAmelCase :       Union[str, Any] 							=		(big_a + 1) + (big_a - 1) * _cos
							UpperCAmelCase :       Optional[Any] 							=		(big_a - 1) - (big_a + 1) * _cos
							UpperCAmelCase :       Union[str, Any] 							=		(big_a - 1) + (big_a + 1) * _cos
							UpperCAmelCase :       List[str] 							=		2 * sqrt(_lowerCAmelCase  ) * alpha

							UpperCAmelCase :       Any 							=		big_a * (ppmc + aaa)
							UpperCAmelCase :       str 							=		-2 * big_a * pmpc
							UpperCAmelCase :       List[Any] 							=		big_a * (ppmc - aaa)
							UpperCAmelCase :       Optional[Any] 							=		pmc + aaa
							UpperCAmelCase :       Any 							=		2 * mpc
							UpperCAmelCase :       str 							=		pmc - aaa

							UpperCAmelCase :       Union[str, Any] 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt





