






from math import pi, sqrt, tan






def 				lowerCamelCase__				(_UpperCAmelCase):
			if side_length < 0:
						raise ValueError('surface_area_cube() only accepts non-negative values')
			return 6 * side_length**2






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase							,       _UpperCAmelCase):
			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__				(_UpperCAmelCase):
			if radius < 0:
						raise ValueError('surface_area_sphere() only accepts non-negative values')
			return 4 * pi * radius**2






def 				lowerCamelCase__				(_UpperCAmelCase):
			if radius < 0:
						raise ValueError('surface_area_hemisphere() only accepts non-negative values')
			return 3 * pi * radius**2






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			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__				(_UpperCAmelCase							,       _UpperCAmelCase							,       _UpperCAmelCase):
			if radius_a < 0 or radius_a < 0 or height < 0:
						raise ValueError(
						    'surface_area_conical_frustum() only accepts non-negative values')
			SCREAMING_SNAKE_CASE						= (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__				(_UpperCAmelCase							,       _UpperCAmelCase):
			if radius < 0 or height < 0:
						raise ValueError('surface_area_cylinder() only accepts non-negative values')
			return 2 * pi * radius * (height + radius)






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			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(_UpperCAmelCase							,       2) * torus_radius * tube_radius






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			if length < 0 or width < 0:
						raise ValueError('area_rectangle() only accepts non-negative values')
			return length * width






def 				lowerCamelCase__				(_UpperCAmelCase):
			if side_length < 0:
						raise ValueError('area_square() only accepts non-negative values')
			return side_length**2






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






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase							,       _UpperCAmelCase):
			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')
			SCREAMING_SNAKE_CASE						= (sidea + sidea + sidea) / 2
			SCREAMING_SNAKE_CASE						= sqrt(
			    semi_perimeter
			    * (semi_perimeter - sidea)
			    * (semi_perimeter - sidea)
			    * (semi_perimeter - sidea))
			return area






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			if base < 0 or height < 0:
						raise ValueError('area_parallelogram() only accepts non-negative values')
			return base * height






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase							,       _UpperCAmelCase):
			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__				(_UpperCAmelCase):
			if radius < 0:
						raise ValueError('area_circle() only accepts non-negative values')
			return pi * radius**2






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			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__				(_UpperCAmelCase							,       _UpperCAmelCase):
			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__				(_UpperCAmelCase							,       _UpperCAmelCase):
			if not isinstance(_UpperCAmelCase							,       _UpperCAmelCase) 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) = }""")












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


if is_vision_available():
				import PIL


a_		:						Optional[int]             =    logging.get_logger(__name__)






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			SCREAMING_SNAKE_CASE						= b.T
			SCREAMING_SNAKE_CASE						= np.sum(np.square(_UpperCAmelCase)							,       axis=1)
			SCREAMING_SNAKE_CASE						= np.sum(np.square(_UpperCAmelCase)							,       axis=0)
			SCREAMING_SNAKE_CASE						= np.matmul(_UpperCAmelCase							,       _UpperCAmelCase)
			SCREAMING_SNAKE_CASE						= aa[:, None] - 2 * ab + ba[None, :]
			return d






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			SCREAMING_SNAKE_CASE						= x.reshape(-1							,       3)
			SCREAMING_SNAKE_CASE						= squared_euclidean_distance(_UpperCAmelCase							,       _UpperCAmelCase)
			return np.argmin(_UpperCAmelCase							,       axis=1)







class 		_snake_case  (  A__					):
			_lowercase		:    str			     =							['''pixel_values''']






			def __init__(       self		,					a = None		,					a = True		,					a = None		,					a = PILImageResampling.BILINEAR		,					a = True		,					a = True		,					**a		,					)      ->       None:
						super().__init__(**a)
						SCREAMING_SNAKE_CASE						= size if size is not None else {'height': 256, 'width': 256}
						SCREAMING_SNAKE_CASE						= get_size_dict(a)
						SCREAMING_SNAKE_CASE						= np.array(a) if clusters is not None else None
						SCREAMING_SNAKE_CASE						= do_resize
						SCREAMING_SNAKE_CASE						= size
						SCREAMING_SNAKE_CASE						= resample
						SCREAMING_SNAKE_CASE						= do_normalize
						SCREAMING_SNAKE_CASE						= do_color_quantize






			def    SCREAMING_SNAKE_CASE__    (       self		,					a		,					a		,					a = PILImageResampling.BILINEAR		,					a = None		,					**a		,					)      ->       np.ndarray:
						SCREAMING_SNAKE_CASE						= get_size_dict(a)
						if "height" not in size or "width" not in size:
									raise ValueError(f'''Size dictionary must contain both height and width keys. Got {size.keys()}''')
						return resize(
						    a		,					size=(size['height'], size['width'])		,					resample=a		,					data_format=a		,					**a)






			def    SCREAMING_SNAKE_CASE__    (       self		,					a		,					a = None		,					)      ->       np.ndarray:
						SCREAMING_SNAKE_CASE						= rescale(image=a		,					scale=1 / 1_27.5		,					data_format=a)
						SCREAMING_SNAKE_CASE						= image - 1
						return image







			def    SCREAMING_SNAKE_CASE__    (       self		,					a		,					a = None		,					a = None		,					a = None		,					a = None		,					a = None		,					a = None		,					a = None		,					a = ChannelDimension.FIRST		,					**a		,					)      ->       PIL.Image.Image:
						SCREAMING_SNAKE_CASE						= do_resize if do_resize is not None else self.do_resize
						SCREAMING_SNAKE_CASE						= size if size is not None else self.size
						SCREAMING_SNAKE_CASE						= get_size_dict(a)
						SCREAMING_SNAKE_CASE						= resample if resample is not None else self.resample
						SCREAMING_SNAKE_CASE						= do_normalize if do_normalize is not None else self.do_normalize
						SCREAMING_SNAKE_CASE						= do_color_quantize if do_color_quantize is not None else self.do_color_quantize
						SCREAMING_SNAKE_CASE						= clusters if clusters is not None else self.clusters
						SCREAMING_SNAKE_CASE						= np.array(a)

						SCREAMING_SNAKE_CASE						= make_list_of_images(a)

						if not valid_images(a):
									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 or resample is None:
									raise ValueError('Size and resample must be specified if do_resize is True.')

						if do_color_quantize and clusters is None:
									raise ValueError('Clusters must be specified if do_color_quantize is True.')

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

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

						if do_normalize:
									SCREAMING_SNAKE_CASE						= [self.normalize(image=a) for image in images]

						if do_color_quantize:
									SCREAMING_SNAKE_CASE						= [to_channel_dimension_format(a		,					ChannelDimension.LAST) for image in images]
									# color quantize from (batch_size, height, width, 3) to (batch_size, height, width)
									SCREAMING_SNAKE_CASE						= np.array(a)
									SCREAMING_SNAKE_CASE						= color_quantize(a		,					a).reshape(images.shape[:-1])

									# flatten to (batch_size, height*width)
									SCREAMING_SNAKE_CASE						= images.shape[0]
									SCREAMING_SNAKE_CASE						= images.reshape(a		,					-1)

									# We need to convert back to a list of images to keep consistent behaviour across processors.
									SCREAMING_SNAKE_CASE						= list(a)
						else:
									SCREAMING_SNAKE_CASE						= [to_channel_dimension_format(a		,					a) for image in images]

						SCREAMING_SNAKE_CASE						= {'input_ids': images}
						return BatchFeature(data=a		,					tensor_type=a)




