
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 normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
    IMAGENET_STANDARD_MEAN,
    IMAGENET_STANDARD_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, logging


__lowerCAmelCase   :     Dict      =						logging.get_logger(__name__)


class   __lowerCAmelCase		(		lowerCAmelCase_ ):



      """simple docstring"""







      A__		:     Union[str, Any]       				=      ['''pixel_values''']




      def __init__( self						:    int			,    _snake_case						:    bool = True			,    _snake_case						:    Optional[Dict[str, int]] = None			,    _snake_case						:    PILImageResampling = PILImageResampling.BILINEAR			,    _snake_case						:    bool = True			,    _snake_case						:    Union[int, float] = 1 / 255			,    _snake_case						:    bool = True			,    _snake_case						:    Optional[Union[float, List[float]]] = None			,    _snake_case						:    Optional[Union[float, List[float]]] = None			,    **_snake_case						:    List[str]			,    ):
          super().__init__(**_snake_case			)
          __lowercase						:     Tuple		      =    size if size is not None else {'''height''': 224, '''width''': 224}
          __lowercase						:     List[str]		      =    get_size_dict(_snake_case			)
          __lowercase						:     Union[str, Any]		      =    do_resize
          __lowercase						:     int		      =    do_rescale
          __lowercase						:     List[Any]		      =    do_normalize
          __lowercase						:     Dict		      =    size
          __lowercase						:     Any		      =    resample
          __lowercase						:     int		      =    rescale_factor
          __lowercase						:     Optional[Any]		      =    image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
          __lowercase						:     Optional[Any]		      =    image_std if image_std is not None else IMAGENET_STANDARD_STD




      def 						snake_case_     ( self						:    int			,    _snake_case						:    np.ndarray			,    _snake_case						:    Dict[str, int]			,    _snake_case						:    PILImageResampling = PILImageResampling.BILINEAR			,    _snake_case						:    Optional[Union[str, ChannelDimension]] = None			,    **_snake_case						:    Optional[int]			,    ):
          __lowercase						:     List[Any]		      =    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()}'			)
          return resize(
              _snake_case			,    size=(size['''height'''], size['''width'''])			,    resample=_snake_case			,    data_format=_snake_case			,    **_snake_case			)




      def 						snake_case_     ( self						:    Union[str, Any]			,    _snake_case						:    np.ndarray			,    _snake_case						:    float			,    _snake_case						:    Optional[Union[str, ChannelDimension]] = None			,    **_snake_case						:    Dict			):
          return rescale(_snake_case			,    scale=_snake_case			,    data_format=_snake_case			,    **_snake_case			)




      def 						snake_case_     ( self						:    Any			,    _snake_case						:    np.ndarray			,    _snake_case						:    Union[float, List[float]]			,    _snake_case						:    Union[float, List[float]]			,    _snake_case						:    Optional[Union[str, ChannelDimension]] = None			,    **_snake_case						:    Any			,    ):
          return normalize(_snake_case			,    mean=_snake_case			,    std=_snake_case			,    data_format=_snake_case			,    **_snake_case			)




      def 						snake_case_     ( self						:    Dict			,    _snake_case						:    ImageInput			,    _snake_case						:    Optional[bool] = None			,    _snake_case						:    Dict[str, int] = None			,    _snake_case						:    PILImageResampling = None			,    _snake_case						:    Optional[bool] = None			,    _snake_case						:    Optional[float] = None			,    _snake_case						:    Optional[bool] = None			,    _snake_case						:    Optional[Union[float, List[float]]] = None			,    _snake_case						:    Optional[Union[float, List[float]]] = None			,    _snake_case						:    Optional[Union[str, TensorType]] = None			,    _snake_case						:    Union[str, ChannelDimension] = ChannelDimension.FIRST			,    **_snake_case						:    str			,    ):
          __lowercase						:     List[Any]		      =    do_resize if do_resize is not None else self.do_resize
          __lowercase						:     Any		      =    do_rescale if do_rescale is not None else self.do_rescale
          __lowercase						:     Optional[Any]		      =    do_normalize if do_normalize is not None else self.do_normalize
          __lowercase						:     Optional[Any]		      =    resample if resample is not None else self.resample
          __lowercase						:     Tuple		      =    rescale_factor if rescale_factor is not None else self.rescale_factor
          __lowercase						:     Dict		      =    image_mean if image_mean is not None else self.image_mean
          __lowercase						:     Any		      =    image_std if image_std is not None else self.image_std

          __lowercase						:     Optional[int]		      =    size if size is not None else self.size
          __lowercase						:     Tuple		      =    get_size_dict(_snake_case			)

          __lowercase						:     Optional[int]		      =    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_rescale and rescale_factor is None:
              raise ValueError('''Rescale factor must be specified if do_rescale is True.'''			)

          # All transformations expect numpy arrays.
          __lowercase						:     Optional[Any]		      =    [to_numpy_array(_snake_case			) for image in images]

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

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

          if do_normalize:
              __lowercase						:     Union[str, Any]		      =    [self.normalize(image=_snake_case			,    mean=_snake_case			,    std=_snake_case			) for image in images]

          __lowercase						:     Tuple		      =    [to_channel_dimension_format(_snake_case			,    _snake_case			) for image in images]

          __lowercase						:     List[str]		      =    {'''pixel_values''': images}
          return BatchFeature(data=_snake_case			,    tensor_type=_snake_case			)




from __future__ import annotations

from math import pi, pow


def       UpperCAmelCase_					(  __lowerCAmelCase		)	->  float:
    if side_length < 0:
        raise ValueError('''vol_cube() only accepts non-negative values'''		)
    return pow(__lowerCAmelCase		,   3		)


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or radius < 0:
        raise ValueError('''vol_spherical_cap() only accepts non-negative values'''		)
    # Volume is 1/3 pi * height squared * (3 * radius - height)
    return 1 / 3 * pi * pow(__lowerCAmelCase		,   2		) * (3 * radius - height)


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if radius_a < 0 or radius_a < 0 or centers_distance < 0:
        raise ValueError('''vol_spheres_intersect() only accepts non-negative values'''		)
    if centers_distance == 0:
        return vol_sphere(min(__lowerCAmelCase		,   __lowerCAmelCase		)		)

    __lowercase						:     Dict		      =    (
        (radius_a - radius_a + centers_distance)
        * (radius_a + radius_a - centers_distance)
        / (2 * centers_distance)
    )
    __lowercase						:     Optional[int]		      =    (
        (radius_a - radius_a + centers_distance)
        * (radius_a + radius_a - centers_distance)
        / (2 * centers_distance)
    )

    return vol_spherical_cap(__lowerCAmelCase		,   __lowerCAmelCase		) + vol_spherical_cap(__lowerCAmelCase		,   __lowerCAmelCase		)


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:

    if radius_a <= 0 or radius_a <= 0 or centers_distance < 0:
        raise ValueError(
            '''vol_spheres_union() only accepts non-negative values, non-zero radius'''		)

    if centers_distance == 0:
        return vol_sphere(max(__lowerCAmelCase		,   __lowerCAmelCase		)		)

    return (
        vol_sphere(__lowerCAmelCase		)
        + vol_sphere(__lowerCAmelCase		)
        - vol_spheres_intersect(__lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)
    )


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if width < 0 or height < 0 or length < 0:
        raise ValueError('''vol_cuboid() only accepts non-negative values'''		)
    return float(width * height * length		)


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or area_of_base < 0:
        raise ValueError('''vol_cone() only accepts non-negative values'''		)
    return area_of_base * height / 3.0


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or radius < 0:
        raise ValueError('''vol_right_circ_cone() only accepts non-negative values'''		)
    return pi * pow(__lowerCAmelCase		,   2		) * height / 3.0


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or area_of_base < 0:
        raise ValueError('''vol_prism() only accepts non-negative values'''		)
    return float(area_of_base * height		)


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or area_of_base < 0:
        raise ValueError('''vol_pyramid() only accepts non-negative values'''		)
    return area_of_base * height / 3.0


def       UpperCAmelCase_					(  __lowerCAmelCase		)	->  float:
    if radius < 0:
        raise ValueError('''vol_sphere() only accepts non-negative values'''		)
    # Volume is 4/3 * pi * radius cubed
    return 4 / 3 * pi * pow(__lowerCAmelCase		,   3		)


def       UpperCAmelCase_					(  __lowerCAmelCase		)	->  float:
    if radius < 0:
        raise ValueError('''vol_hemisphere() only accepts non-negative values'''		)
    # Volume is radius cubed * pi * 2/3
    return pow(__lowerCAmelCase		,   3		) * pi * 2 / 3


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if height < 0 or radius < 0:
        raise ValueError('''vol_circular_cylinder() only accepts non-negative values'''		)
    # Volume is radius squared * height * pi
    return pow(__lowerCAmelCase		,   2		) * height * pi


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    # Volume - (outer_radius squared - inner_radius squared) * pi * height
    if inner_radius < 0 or outer_radius < 0 or height < 0:
        raise ValueError(
            '''vol_hollow_circular_cylinder() only accepts non-negative values'''		)
    if outer_radius <= inner_radius:
        raise ValueError('''outer_radius must be greater than inner_radius'''		)
    return pi * (pow(__lowerCAmelCase		,   2		) - pow(__lowerCAmelCase		,   2		)) * height


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    # Volume is 1/3 * pi * height *
    #           (radius_1 squared + radius_2 squared + radius_1 * radius_2)
    if radius_a < 0 or radius_a < 0 or height < 0:
        raise ValueError('''vol_conical_frustum() only accepts non-negative values'''		)
    return (
        1
        / 3
        * pi
        * height
        * (pow(__lowerCAmelCase		,   2		) + pow(__lowerCAmelCase		,   2		) + radius_a * radius_a)
    )


def       UpperCAmelCase_					(  __lowerCAmelCase		,   __lowerCAmelCase		)	->  float:
    if torus_radius < 0 or tube_radius < 0:
        raise ValueError('''vol_torus() only accepts non-negative values'''		)
    return 2 * pow(__lowerCAmelCase		,   2		) * torus_radius * pow(__lowerCAmelCase		,   2		)


def       UpperCAmelCase_					(  )	->  Optional[Any]:
    print('''Volumes:'''		)
    print(F'Cube: {vol_cube(2		) = }'		)  # = 8
    print(F'Cuboid: {vol_cuboid(2		,   2		,   2		) = }'		)  # = 8
    print(F'Cone: {vol_cone(2		,   2		) = }'		)  # ~= 1.33
    print(F'Right Circular Cone: {vol_right_circ_cone(2		,   2		) = }'		)  # ~= 8.38
    print(F'Prism: {vol_prism(2		,   2		) = }'		)  # = 4
    print(F'Pyramid: {vol_pyramid(2		,   2		) = }'		)  # ~= 1.33
    print(F'Sphere: {vol_sphere(2		) = }'		)  # ~= 33.5
    print(F'Hemisphere: {vol_hemisphere(2		) = }'		)  # ~= 16.75
    print(F'Circular Cylinder: {vol_circular_cylinder(2		,   2		) = }'		)  # ~= 25.1
    print(F'Torus: {vol_torus(2		,   2		) = }'		)  # ~= 157.9
    print(F'Conical Frustum: {vol_conical_frustum(2		,   2		,   4		) = }'		)  # ~= 58.6
    print(F'Spherical cap: {vol_spherical_cap(1		,   2		) = }'		)  # ~= 5.24
    print(F'Spheres intersetion: {vol_spheres_intersect(2		,   2		,   1		) = }'		)  # ~= 21.21
    print(F'Spheres union: {vol_spheres_union(2		,   2		,   1		) = }'		)  # ~= 45.81
    print(
        F'Hollow Circular Cylinder: {vol_hollow_circular_cylinder(1		,   2		,   3		) = }'		)  # ~= 28.3


if __name__ == "__main__":
 main()


