
"""simple docstring"""





from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
    center_crop,
    convert_to_rgb,
    get_resize_output_image_size,
    normalize,
    rescale,
    resize,
    to_channel_dimension_format,
)
from ...image_utils import (
    OPENAI_CLIP_MEAN,
    OPENAI_CLIP_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


_a														=		logging.get_logger(__name__)


if is_vision_available():
				import PIL






class     _UpperCAmelCase(    lowerCamelCase	):
		lowercase__						=      ['pixel_values']



		def __init__(					self				,		__a = True				,		__a = None				,		__a = PILImageResampling.BICUBIC				,		__a = True				,		__a = None				,		__a = True				,		__a = 1 / 2_55				,		__a = True				,		__a = None				,		__a = None				,		__a = True				,		**__a				,		)       ->       None:






							'''simple docstring'''
							super().__init__(**_snake_case)
							_UpperCamelCase							 =  size if size is not None else {'''shortest_edge''': 2_24}
							_UpperCamelCase							 =  get_size_dict(_snake_case				,		default_to_square=_snake_case)
							_UpperCamelCase							 =  crop_size if crop_size is not None else {'''height''': 2_24, '''width''': 2_24}
							_UpperCamelCase							 =  get_size_dict(_snake_case				,		default_to_square=_snake_case				,		param_name='''crop_size''')

							_UpperCamelCase							 =  do_resize
							_UpperCamelCase							 =  size
							_UpperCamelCase							 =  resample
							_UpperCamelCase							 =  do_center_crop
							_UpperCamelCase							 =  crop_size
							_UpperCamelCase							 =  do_rescale
							_UpperCamelCase							 =  rescale_factor
							_UpperCamelCase							 =  do_normalize
							_UpperCamelCase							 =  image_mean if image_mean is not None else OPENAI_CLIP_MEAN
							_UpperCamelCase							 =  image_std if image_std is not None else OPENAI_CLIP_STD
							_UpperCamelCase							 =  do_convert_rgb



		def 						UpperCAmelCase							(					self				,		__a				,		__a				,		__a = PILImageResampling.BICUBIC				,		__a = None				,		**__a				,		)       ->       np.ndarray:






							'''simple docstring'''
							_UpperCamelCase							 =  get_size_dict(_snake_case				,		default_to_square=_snake_case)
							if "shortest_edge" not in size:
												raise ValueError(F'''The `size` parameter must contain the key `shortest_edge`. Got {size.keys()}''')
							_UpperCamelCase							 =  get_resize_output_image_size(_snake_case				,		size=size['''shortest_edge''']				,		default_to_square=_snake_case)
							return resize(_snake_case				,		size=_snake_case				,		resample=_snake_case				,		data_format=_snake_case				,		**_snake_case)



		def 						UpperCAmelCase							(					self				,		__a				,		__a				,		__a = None				,		**__a				,		)       ->       np.ndarray:






							'''simple docstring'''
							_UpperCamelCase							 =  get_size_dict(_snake_case)
							if "height" not in size or "width" not in size:
												raise ValueError(F'''The `size` parameter must contain the keys (height, width). Got {size.keys()}''')
							return center_crop(_snake_case				,		size=(size['''height'''], size['''width'''])				,		data_format=_snake_case				,		**_snake_case)



		def 						UpperCAmelCase							(					self				,		__a				,		__a				,		__a = None				,		**__a				,		)       ->       Tuple:






							'''simple docstring'''
							return rescale(_snake_case				,		scale=_snake_case				,		data_format=_snake_case				,		**_snake_case)



		def 						UpperCAmelCase							(					self				,		__a				,		__a				,		__a				,		__a = None				,		**__a				,		)       ->       np.ndarray:






							'''simple docstring'''
							return normalize(_snake_case				,		mean=_snake_case				,		std=_snake_case				,		data_format=_snake_case				,		**_snake_case)




		def 						UpperCAmelCase							(					self				,		__a				,		__a = None				,		__a = None				,		__a = None				,		__a = None				,		__a = None				,		__a = None				,		__a = None				,		__a = None				,		__a = None				,		__a = None				,		__a = None				,		__a = None				,		__a = ChannelDimension.FIRST				,		**__a				,		)       ->       PIL.Image.Image:






							'''simple docstring'''
							_UpperCamelCase							 =  do_resize if do_resize is not None else self.do_resize
							_UpperCamelCase							 =  size if size is not None else self.size
							_UpperCamelCase							 =  get_size_dict(_snake_case				,		param_name='''size'''				,		default_to_square=_snake_case)
							_UpperCamelCase							 =  resample if resample is not None else self.resample
							_UpperCamelCase							 =  do_center_crop if do_center_crop is not None else self.do_center_crop
							_UpperCamelCase							 =  crop_size if crop_size is not None else self.crop_size
							_UpperCamelCase							 =  get_size_dict(_snake_case				,		param_name='''crop_size'''				,		default_to_square=_snake_case)
							_UpperCamelCase							 =  do_rescale if do_rescale is not None else self.do_rescale
							_UpperCamelCase							 =  rescale_factor if rescale_factor is not None else self.rescale_factor
							_UpperCamelCase							 =  do_normalize if do_normalize is not None else self.do_normalize
							_UpperCamelCase							 =  image_mean if image_mean is not None else self.image_mean
							_UpperCamelCase							 =  image_std if image_std is not None else self.image_std
							_UpperCamelCase							 =  do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

							_UpperCamelCase							 =  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.''')

							if do_center_crop and crop_size is None:
												raise ValueError('''Crop size must be specified if do_center_crop is True.''')

							if do_rescale and rescale_factor is None:
												raise ValueError('''Rescale factor must be specified if do_rescale is True.''')

							if do_normalize and (image_mean is None or image_std is None):
												raise ValueError('''Image mean and std must be specified if do_normalize is True.''')

							# PIL RGBA images are converted to RGB
							if do_convert_rgb:
												_UpperCamelCase							 =  [convert_to_rgb(_snake_case) for image in images]

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

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

							if do_center_crop:
												_UpperCamelCase							 =  [self.center_crop(image=_snake_case				,		size=_snake_case) for image in images]

							if do_rescale:
												_UpperCamelCase							 =  [self.rescale(image=_snake_case				,		scale=_snake_case) for image in images]

							if do_normalize:
												_UpperCamelCase							 =  [self.normalize(image=_snake_case				,		mean=_snake_case				,		std=_snake_case) for image in images]

							_UpperCamelCase							 =  [to_channel_dimension_format(_snake_case				,		_snake_case) for image in images]

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








from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter


def     __lowerCAmelCase			(			a__						,    a__						,    a__ = 1 / sqrt(2  )  )       ->  IIRFilter:
				__a										=    tau * frequency / samplerate
				__a										=    sin(a__  )
				__a										=    cos(a__  )
				__a										=    _sin / (2 * q_factor)

				__a										=    (1 - _cos) / 2
				__a										=    1 - _cos

				__a										=    1 + alpha
				__a										=    -2 * _cos
				__a										=    1 - alpha

				__a										=    IIRFilter(2  )
				filt.set_coefficients([aa, aa, aa]						,    [ba, ba, ba]  )
				return filt


def     __lowerCAmelCase			(			a__						,    a__						,    a__ = 1 / sqrt(2  )  )       ->  IIRFilter:
				__a										=    tau * frequency / samplerate
				__a										=    sin(a__  )
				__a										=    cos(a__  )
				__a										=    _sin / (2 * q_factor)

				__a										=    (1 + _cos) / 2
				__a										=    -1 - _cos

				__a										=    1 + alpha
				__a										=    -2 * _cos
				__a										=    1 - alpha

				__a										=    IIRFilter(2  )
				filt.set_coefficients([aa, aa, aa]						,    [ba, ba, ba]  )
				return filt


def     __lowerCAmelCase			(			a__						,    a__						,    a__ = 1 / sqrt(2  )  )       ->  IIRFilter:
				__a										=    tau * frequency / samplerate
				__a										=    sin(a__  )
				__a										=    cos(a__  )
				__a										=    _sin / (2 * q_factor)

				__a										=    _sin / 2
				__a										=    0
				__a										=    -ba

				__a										=    1 + alpha
				__a										=    -2 * _cos
				__a										=    1 - alpha

				__a										=    IIRFilter(2  )
				filt.set_coefficients([aa, aa, aa]						,    [ba, ba, ba]  )
				return filt


def     __lowerCAmelCase			(			a__						,    a__						,    a__ = 1 / sqrt(2  )  )       ->  IIRFilter:
				__a										=    tau * frequency / samplerate
				__a										=    sin(a__  )
				__a										=    cos(a__  )
				__a										=    _sin / (2 * q_factor)

				__a										=    1 - alpha
				__a										=    -2 * _cos
				__a										=    1 + alpha

				__a										=    IIRFilter(2  )
				filt.set_coefficients([ba, ba, ba]						,    [ba, ba, ba]  )
				return filt


def     __lowerCAmelCase			(			a__						,    a__						,    a__						,    a__ = 1 / sqrt(2  )						,    )       ->  IIRFilter:
				__a										=    tau * frequency / samplerate
				__a										=    sin(a__  )
				__a										=    cos(a__  )
				__a										=    _sin / (2 * q_factor)
				__a										=    10 ** (gain_db / 40)

				__a										=    1 + alpha * big_a
				__a										=    -2 * _cos
				__a										=    1 - alpha * big_a
				__a										=    1 + alpha / big_a
				__a										=    -2 * _cos
				__a										=    1 - alpha / big_a

				__a										=    IIRFilter(2  )
				filt.set_coefficients([aa, aa, aa]						,    [ba, ba, ba]  )
				return filt


def     __lowerCAmelCase			(			a__						,    a__						,    a__						,    a__ = 1 / sqrt(2  )						,    )       ->  IIRFilter:
				__a										=    tau * frequency / samplerate
				__a										=    sin(a__  )
				__a										=    cos(a__  )
				__a										=    _sin / (2 * q_factor)
				__a										=    10 ** (gain_db / 40)
				__a										=    (big_a + 1) - (big_a - 1) * _cos
				__a										=    (big_a + 1) + (big_a - 1) * _cos
				__a										=    (big_a - 1) - (big_a + 1) * _cos
				__a										=    (big_a - 1) + (big_a + 1) * _cos
				__a										=    2 * sqrt(a__  ) * alpha

				__a										=    big_a * (pmc + aaa)
				__a										=    2 * big_a * mpc
				__a										=    big_a * (pmc - aaa)
				__a										=    ppmc + aaa
				__a										=    -2 * pmpc
				__a										=    ppmc - aaa

				__a										=    IIRFilter(2  )
				filt.set_coefficients([aa, aa, aa]						,    [ba, ba, ba]  )
				return filt






def     __lowerCAmelCase			(			a__						,    a__						,    a__						,    a__ = 1 / sqrt(2  )						,    )       ->  IIRFilter:
				__a										=    tau * frequency / samplerate
				__a										=    sin(a__  )
				__a										=    cos(a__  )
				__a										=    _sin / (2 * q_factor)
				__a										=    10 ** (gain_db / 40)
				__a										=    (big_a + 1) - (big_a - 1) * _cos
				__a										=    (big_a + 1) + (big_a - 1) * _cos
				__a										=    (big_a - 1) - (big_a + 1) * _cos
				__a										=    (big_a - 1) + (big_a + 1) * _cos
				__a										=    2 * sqrt(a__  ) * alpha

				__a										=    big_a * (ppmc + aaa)
				__a										=    -2 * big_a * pmpc
				__a										=    big_a * (ppmc - aaa)
				__a										=    pmc + aaa
				__a										=    2 * mpc
				__a										=    pmc - aaa

				__a										=    IIRFilter(2  )
				filt.set_coefficients([aa, aa, aa]						,    [ba, ba, ba]  )
				return filt