





'''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


lowercase__   :				List[Any]      =   logging.get_logger(__name__)


if is_vision_available():
  import PIL


class 			SCREAMING_SNAKE_CASE   (a__							):
     lowerCAmelCase		      =	['''pixel_values''']


     def __init__(						self						,     _UpperCAmelCase = True						,     _UpperCAmelCase = None						,     _UpperCAmelCase = PILImageResampling.BICUBIC						,     _UpperCAmelCase = True						,     _UpperCAmelCase = None						,     _UpperCAmelCase = True						,     _UpperCAmelCase = 1 / 255						,     _UpperCAmelCase = True						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = True						,     **_UpperCAmelCase						,     ):

          '''simple docstring'''






          super().__init__(**_UpperCAmelCase)
          __A						:			Dict								=	size if size is not None else {'shortest_edge': 224}
          __A						:			int								=	get_size_dict(_UpperCAmelCase						,     default_to_square=_UpperCAmelCase)
          __A						:			Union[str, Any]								=	crop_size if crop_size is not None else {'height': 224, 'width': 224}
          __A						:			List[Any]								=	get_size_dict(_UpperCAmelCase						,     default_to_square=_UpperCAmelCase						,     param_name='crop_size')

          __A						:			Optional[int]								=	do_resize
          __A						:			Optional[int]								=	size
          __A						:			Any								=	resample
          __A						:			Any								=	do_center_crop
          __A						:			str								=	crop_size
          __A						:			Dict								=	do_rescale
          __A						:			Dict								=	rescale_factor
          __A						:			Optional[int]								=	do_normalize
          __A						:			Any								=	image_mean if image_mean is not None else OPENAI_CLIP_MEAN
          __A						:			Optional[Any]								=	image_std if image_std is not None else OPENAI_CLIP_STD
          __A						:			Optional[Any]								=	do_convert_rgb


     def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase						,     _UpperCAmelCase						,     _UpperCAmelCase = PILImageResampling.BICUBIC						,     _UpperCAmelCase = None						,     **_UpperCAmelCase						,     ):

          '''simple docstring'''






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


     def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase						,     _UpperCAmelCase						,     _UpperCAmelCase = None						,     **_UpperCAmelCase						,     ):

          '''simple docstring'''






          __A						:			List[str]								=	get_size_dict(_UpperCAmelCase)
          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(_UpperCAmelCase						,     size=(size['height'], size['width'])						,     data_format=_UpperCAmelCase						,     **_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase						,     _UpperCAmelCase						,     _UpperCAmelCase = None						,     **_UpperCAmelCase						,     ):

          '''simple docstring'''






          return rescale(_UpperCAmelCase						,     scale=_UpperCAmelCase						,     data_format=_UpperCAmelCase						,     **_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase						,     _UpperCAmelCase						,     _UpperCAmelCase						,     _UpperCAmelCase = None						,     **_UpperCAmelCase						,     ):

          '''simple docstring'''






          return normalize(_UpperCAmelCase						,     mean=_UpperCAmelCase						,     std=_UpperCAmelCase						,     data_format=_UpperCAmelCase						,     **_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = None						,     _UpperCAmelCase = ChannelDimension.FIRST						,     **_UpperCAmelCase						,     ):

          '''simple docstring'''






          __A						:			Optional[Any]								=	do_resize if do_resize is not None else self.do_resize
          __A						:			List[Any]								=	size if size is not None else self.size
          __A						:			Tuple								=	get_size_dict(_UpperCAmelCase						,     param_name='size'						,     default_to_square=_UpperCAmelCase)
          __A						:			Any								=	resample if resample is not None else self.resample
          __A						:			Any								=	do_center_crop if do_center_crop is not None else self.do_center_crop
          __A						:			Tuple								=	crop_size if crop_size is not None else self.crop_size
          __A						:			Union[str, Any]								=	get_size_dict(_UpperCAmelCase						,     param_name='crop_size'						,     default_to_square=_UpperCAmelCase)
          __A						:			Optional[int]								=	do_rescale if do_rescale is not None else self.do_rescale
          __A						:			List[str]								=	rescale_factor if rescale_factor is not None else self.rescale_factor
          __A						:			str								=	do_normalize if do_normalize is not None else self.do_normalize
          __A						:			Tuple								=	image_mean if image_mean is not None else self.image_mean
          __A						:			List[Any]								=	image_std if image_std is not None else self.image_std
          __A						:			int								=	do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

          __A						:			List[str]								=	make_list_of_images(_UpperCAmelCase)

          if not valid_images(_UpperCAmelCase):
               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:
               __A						:			List[str]								=	[convert_to_rgb(_UpperCAmelCase) for image in images]

          # All transformations expect numpy arrays.
          __A						:			Optional[int]								=	[to_numpy_array(_UpperCAmelCase) for image in images]

          if do_resize:
               __A						:			Union[str, Any]								=	[self.resize(image=_UpperCAmelCase						,     size=_UpperCAmelCase						,     resample=_UpperCAmelCase) for image in images]

          if do_center_crop:
               __A						:			Union[str, Any]								=	[self.center_crop(image=_UpperCAmelCase						,     size=_UpperCAmelCase) for image in images]

          if do_rescale:
               __A						:			Union[str, Any]								=	[self.rescale(image=_UpperCAmelCase						,     scale=_UpperCAmelCase) for image in images]

          if do_normalize:
               __A						:			Dict								=	[self.normalize(image=_UpperCAmelCase						,     mean=_UpperCAmelCase						,     std=_UpperCAmelCase) for image in images]

          __A						:			Union[str, Any]								=	[to_channel_dimension_format(_UpperCAmelCase						,     _UpperCAmelCase) for image in images]

          __A						:			int								=	{'pixel_values': images}
          return BatchFeature(data=_UpperCAmelCase						,     tensor_type=_UpperCAmelCase)






'''simple docstring'''




from math import pi, sqrt, tan






def 	_lowerCAmelCase      (  __snake_case  :			float      )					->					float:
     if side_length < 0:
          raise ValueError('surface_area_cube() only accepts non-negative values'      )
     return 6 * side_length**2






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if length < 0 or breadth < 0 or height < 0:
          raise ValueError('surface_area_cuboid() only accepts non-negative values'      )
     return 2 * ((length * breadth) + (breadth * height) + (length * height))






def 	_lowerCAmelCase      (  __snake_case  :			float      )					->					float:
     if radius < 0:
          raise ValueError('surface_area_sphere() only accepts non-negative values'      )
     return 4 * pi * radius**2






def 	_lowerCAmelCase      (  __snake_case  :			float      )					->					float:
     if radius < 0:
          raise ValueError('surface_area_hemisphere() only accepts non-negative values'      )
     return 3 * pi * radius**2






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if radius < 0 or height < 0:
          raise ValueError('surface_area_cone() only accepts non-negative values'      )
     return pi * radius * (radius + (height**2 + radius**2) ** 0.5)






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if radius_a < 0 or radius_a < 0 or height < 0:
          raise ValueError(
              'surface_area_conical_frustum() only accepts non-negative values'      )
     __A						:			Union[str, Any]								=	(height**2 + (radius_a - radius_a) ** 2) ** 0.5
     return pi * ((slant_height * (radius_a + radius_a)) + radius_a**2 + radius_a**2)






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if radius < 0 or height < 0:
          raise ValueError('surface_area_cylinder() only accepts non-negative values'      )
     return 2 * pi * radius * (height + radius)






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if torus_radius < 0 or tube_radius < 0:
          raise ValueError('surface_area_torus() only accepts non-negative values'      )
     if torus_radius < tube_radius:
          raise ValueError(
              'surface_area_torus() does not support spindle or self intersecting tori'      )
     return 4 * pow(__snake_case			,							2      ) * torus_radius * tube_radius






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if length < 0 or width < 0:
          raise ValueError('area_rectangle() only accepts non-negative values'      )
     return length * width






def 	_lowerCAmelCase      (  __snake_case  :			float      )					->					float:
     if side_length < 0:
          raise ValueError('area_square() only accepts non-negative values'      )
     return side_length**2






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if base < 0 or height < 0:
          raise ValueError('area_triangle() only accepts non-negative values'      )
     return (base * height) / 2






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if sidea < 0 or sidea < 0 or sidea < 0:
          raise ValueError('area_triangle_three_sides() only accepts non-negative values'      )
     elif sidea + sidea < sidea or sidea + sidea < sidea or sidea + sidea < sidea:
          raise ValueError('Given three sides do not form a triangle'      )
     __A						:			int								=	(sidea + sidea + sidea) / 2
     __A						:			Tuple								=	sqrt(
         semi_perimeter
         * (semi_perimeter - sidea)
         * (semi_perimeter - sidea)
         * (semi_perimeter - sidea)      )
     return area






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if base < 0 or height < 0:
          raise ValueError('area_parallelogram() only accepts non-negative values'      )
     return base * height






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if basea < 0 or basea < 0 or height < 0:
          raise ValueError('area_trapezium() only accepts non-negative values'      )
     return 1 / 2 * (basea + basea) * height






def 	_lowerCAmelCase      (  __snake_case  :			float      )					->					float:
     if radius < 0:
          raise ValueError('area_circle() only accepts non-negative values'      )
     return pi * radius**2






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if radius_x < 0 or radius_y < 0:
          raise ValueError('area_ellipse() only accepts non-negative values'      )
     return pi * radius_x * radius_y






def 	_lowerCAmelCase      (  __snake_case  :			float			,							__snake_case  :			float      )					->					float:
     if diagonal_a < 0 or diagonal_a < 0:
          raise ValueError('area_rhombus() only accepts non-negative values'      )
     return 1 / 2 * diagonal_a * diagonal_a






def 	_lowerCAmelCase      (  __snake_case  :			int			,							__snake_case  :			float      )					->					float:
     if not isinstance(__snake_case			,							__snake_case      ) or sides < 3:
          raise ValueError(
              'area_reg_polygon() only accepts integers greater than or \
equal to three as number of sides'      )
     elif length < 0:
          raise ValueError(
              'area_reg_polygon() only accepts non-negative values as \
length of a side'      )
     return (sides * length**2) / (4 * tan(pi / sides      ))
     return (sides * length**2) / (4 * tan(pi / sides      ))


if __name__ == "__main__":
  import doctest

  doctest.testmod(verbose=True)  # verbose so we can see methods missing tests

  print('''[DEMO] Areas of various geometric shapes: \n''')
  print(f"""Rectangle: {area_rectangle(10, 20) = }""")
  print(f"""Square: {area_square(10) = }""")
  print(f"""Triangle: {area_triangle(10, 10) = }""")
  print(f"""Triangle: {area_triangle_three_sides(5, 12, 13) = }""")
  print(f"""Parallelogram: {area_parallelogram(10, 20) = }""")
  print(f"""Rhombus: {area_rhombus(10, 20) = }""")
  print(f"""Trapezium: {area_trapezium(10, 20, 30) = }""")
  print(f"""Circle: {area_circle(20) = }""")
  print(f"""Ellipse: {area_ellipse(10, 20) = }""")
  print('''\nSurface Areas of various geometric shapes: \n''')
  print(f"""Cube: {surface_area_cube(20) = }""")
  print(f"""Cuboid: {surface_area_cuboid(10, 20, 30) = }""")
  print(f"""Sphere: {surface_area_sphere(20) = }""")
  print(f"""Hemisphere: {surface_area_hemisphere(20) = }""")
  print(f"""Cone: {surface_area_cone(10, 20) = }""")
  print(f"""Conical Frustum: {surface_area_conical_frustum(10, 20, 30) = }""")
  print(f"""Cylinder: {surface_area_cylinder(10, 20) = }""")
  print(f"""Torus: {surface_area_torus(20, 10) = }""")
  print(f"""Equilateral Triangle: {area_reg_polygon(3, 10) = }""")
  print(f"""Square: {area_reg_polygon(4, 10) = }""")
  print(f"""Reqular Pentagon: {area_reg_polygon(5, 10) = }""")