






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


__snake_case			:			List[str]			   =   logging.get_logger(__name__)


class 			__SCREAMING_SNAKE_CASE    (      __lowercase):
						_SCREAMING_SNAKE_CASE		:				List[Any]            =    ['''pixel_values''']






						def __init__(		self   ,  _UpperCamelCase = True   ,  _UpperCamelCase = None   ,  _UpperCamelCase = PILImageResampling.BILINEAR   ,  _UpperCamelCase = True   ,  _UpperCamelCase = 1 / 2_55   ,  _UpperCamelCase = True   ,  _UpperCamelCase = None   ,  _UpperCamelCase = None   ,  **_UpperCamelCase   ,  ):






												"""simple docstring"""
												super().__init__(**_UpperCamelCase      )
												lowerCAmelCase__			  =  size if size is not None else {'height': 2_24, 'width': 2_24}
												lowerCAmelCase__			  =  get_size_dict(_UpperCamelCase      )
												lowerCAmelCase__			  =  do_resize
												lowerCAmelCase__			  =  do_rescale
												lowerCAmelCase__			  =  do_normalize
												lowerCAmelCase__			  =  size
												lowerCAmelCase__			  =  resample
												lowerCAmelCase__			  =  rescale_factor
												lowerCAmelCase__			  =  image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
												lowerCAmelCase__			  =  image_std if image_std is not None else IMAGENET_STANDARD_STD






						def 					UpperCamelCase__					(		self   ,  _UpperCamelCase   ,  _UpperCamelCase   ,  _UpperCamelCase = PILImageResampling.BILINEAR   ,  _UpperCamelCase = None   ,  **_UpperCamelCase   ,  ):






												"""simple docstring"""
												lowerCAmelCase__			  =  get_size_dict(_UpperCamelCase      )
												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(
												    _UpperCamelCase   ,  size=(size['height'], size['width'])   ,  resample=_UpperCamelCase   ,  data_format=_UpperCamelCase   ,  **_UpperCamelCase      )






						def 					UpperCamelCase__					(		self   ,  _UpperCamelCase   ,  _UpperCamelCase   ,  _UpperCamelCase = None   ,  **_UpperCamelCase      ):






												"""simple docstring"""
												return rescale(_UpperCamelCase   ,  scale=_UpperCamelCase   ,  data_format=_UpperCamelCase   ,  **_UpperCamelCase      )






						def 					UpperCamelCase__					(		self   ,  _UpperCamelCase   ,  _UpperCamelCase   ,  _UpperCamelCase   ,  _UpperCamelCase = None   ,  **_UpperCamelCase   ,  ):






												"""simple docstring"""
												return normalize(_UpperCamelCase   ,  mean=_UpperCamelCase   ,  std=_UpperCamelCase   ,  data_format=_UpperCamelCase   ,  **_UpperCamelCase      )







						def 					UpperCamelCase__					(		self   ,  _UpperCamelCase   ,  _UpperCamelCase = None   ,  _UpperCamelCase = None   ,  _UpperCamelCase = None   ,  _UpperCamelCase = None   ,  _UpperCamelCase = None   ,  _UpperCamelCase = None   ,  _UpperCamelCase = None   ,  _UpperCamelCase = None   ,  _UpperCamelCase = None   ,  _UpperCamelCase = ChannelDimension.FIRST   ,  **_UpperCamelCase   ,  ):






												"""simple docstring"""
												lowerCAmelCase__			  =  do_resize if do_resize is not None else self.do_resize
												lowerCAmelCase__			  =  do_rescale if do_rescale is not None else self.do_rescale
												lowerCAmelCase__			  =  do_normalize if do_normalize is not None else self.do_normalize
												lowerCAmelCase__			  =  resample if resample is not None else self.resample
												lowerCAmelCase__			  =  rescale_factor if rescale_factor is not None else self.rescale_factor
												lowerCAmelCase__			  =  image_mean if image_mean is not None else self.image_mean
												lowerCAmelCase__			  =  image_std if image_std is not None else self.image_std

												lowerCAmelCase__			  =  size if size is not None else self.size
												lowerCAmelCase__			  =  get_size_dict(_UpperCamelCase      )

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

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

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

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

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

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

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













def 		_UpperCamelCase      (			UpperCamelCase_				:    float			,				UpperCamelCase_				:    float			,				UpperCamelCase_				:    float						)     ->      list[int]:

						"""simple docstring"""



						if hue < 0 or hue > 360:
												raise Exception('hue should be between 0 and 360'						)

						if saturation < 0 or saturation > 1:
												raise Exception('saturation should be between 0 and 1'						)

						if value < 0 or value > 1:
												raise Exception('value should be between 0 and 1'						)

						lowerCAmelCase__			  =  value * saturation
						lowerCAmelCase__			  =  hue / 60
						lowerCAmelCase__			  =  chroma * (1 - abs(hue_section % 2 - 1						))
						lowerCAmelCase__			  =  value - chroma

						if hue_section >= 0 and hue_section <= 1:
												lowerCAmelCase__			  =  round(255 * (chroma + match_value)						)
												lowerCAmelCase__			  =  round(255 * (second_largest_component + match_value)						)
												lowerCAmelCase__			  =  round(255 * (match_value)						)
						elif hue_section > 1 and hue_section <= 2:
												lowerCAmelCase__			  =  round(255 * (second_largest_component + match_value)						)
												lowerCAmelCase__			  =  round(255 * (chroma + match_value)						)
												lowerCAmelCase__			  =  round(255 * (match_value)						)
						elif hue_section > 2 and hue_section <= 3:
												lowerCAmelCase__			  =  round(255 * (match_value)						)
												lowerCAmelCase__			  =  round(255 * (chroma + match_value)						)
												lowerCAmelCase__			  =  round(255 * (second_largest_component + match_value)						)
						elif hue_section > 3 and hue_section <= 4:
												lowerCAmelCase__			  =  round(255 * (match_value)						)
												lowerCAmelCase__			  =  round(255 * (second_largest_component + match_value)						)
												lowerCAmelCase__			  =  round(255 * (chroma + match_value)						)
						elif hue_section > 4 and hue_section <= 5:
												lowerCAmelCase__			  =  round(255 * (second_largest_component + match_value)						)
												lowerCAmelCase__			  =  round(255 * (match_value)						)
												lowerCAmelCase__			  =  round(255 * (chroma + match_value)						)
						else:
												lowerCAmelCase__			  =  round(255 * (chroma + match_value)						)
												lowerCAmelCase__			  =  round(255 * (match_value)						)
												lowerCAmelCase__			  =  round(255 * (second_largest_component + match_value)						)

						return [red, green, blue]







def 		_UpperCamelCase      (			UpperCamelCase_				:    int			,				UpperCamelCase_				:    int			,				UpperCamelCase_				:    int						)     ->      list[float]:

						"""simple docstring"""



						if red < 0 or red > 255:
												raise Exception('red should be between 0 and 255'						)

						if green < 0 or green > 255:
												raise Exception('green should be between 0 and 255'						)

						if blue < 0 or blue > 255:
												raise Exception('blue should be between 0 and 255'						)

						lowerCAmelCase__			  =  red / 255
						lowerCAmelCase__			  =  green / 255
						lowerCAmelCase__			  =  blue / 255
						lowerCAmelCase__			  =  max(UpperCamelCase_			,				UpperCamelCase_			,				UpperCamelCase_						)
						lowerCAmelCase__			  =  value - min(UpperCamelCase_			,				UpperCamelCase_			,				UpperCamelCase_						)
						lowerCAmelCase__			  =  0 if value == 0 else chroma / value

						if chroma == 0:
												lowerCAmelCase__			  =  0.0
						elif value == float_red:
												lowerCAmelCase__			  =  60 * (0 + (float_green - float_blue) / chroma)
						elif value == float_green:
												lowerCAmelCase__			  =  60 * (2 + (float_blue - float_red) / chroma)
						else:
												lowerCAmelCase__			  =  60 * (4 + (float_red - float_green) / chroma)

						lowerCAmelCase__			  =  (hue + 360) % 360

						return [hue, saturation, value]







def 		_UpperCamelCase      (			UpperCamelCase_				:    list[float]			,				UpperCamelCase_				:    list[float]						)     ->      bool:

						"""simple docstring"""



						lowerCAmelCase__			  =  abs(hsv_a[0] - hsv_a[0]						) < 0.2
						lowerCAmelCase__			  =  abs(hsv_a[1] - hsv_a[1]						) < 0.002
						lowerCAmelCase__			  =  abs(hsv_a[2] - hsv_a[2]						) < 0.002

						return check_hue and check_saturation and check_value





