






"""simple docstring"""




import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType







class       UpperCAmelCase_						( lowercase			):



      """simple docstring"""
      UpperCamelCase_    : int									=['image_processor', 'tokenizer']
      UpperCamelCase_    : Optional[Any]									='LayoutLMv2ImageProcessor'
      UpperCamelCase_    : Optional[int]									=('LayoutLMv2Tokenizer', 'LayoutLMv2TokenizerFast')
      def __init__(    self   ,    SCREAMING_SNAKE_CASE_=None   ,    SCREAMING_SNAKE_CASE_=None   ,    **SCREAMING_SNAKE_CASE_			)    ->				List[str]:
          UpperCamelCase	:Optional[int]     							=       None
          if "feature_extractor" in kwargs:
              warnings.warn(
                  '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
                  ''' instead.'''   ,    SCREAMING_SNAKE_CASE_   ,    )
              UpperCamelCase	:Optional[int]     							=       kwargs.pop('''feature_extractor'''			)

          UpperCamelCase	:Union[str, Any]     							=       image_processor if image_processor is not None else feature_extractor
          if image_processor is None:
              raise ValueError('''You need to specify an `image_processor`.'''			)
          if tokenizer is None:
              raise ValueError('''You need to specify a `tokenizer`.'''			)

          super().__init__(SCREAMING_SNAKE_CASE_   ,    SCREAMING_SNAKE_CASE_			)
      def __call__(    self   ,    SCREAMING_SNAKE_CASE_   ,    SCREAMING_SNAKE_CASE_ = None   ,    SCREAMING_SNAKE_CASE_ = None   ,    SCREAMING_SNAKE_CASE_ = None   ,    SCREAMING_SNAKE_CASE_ = None   ,    SCREAMING_SNAKE_CASE_ = True   ,    SCREAMING_SNAKE_CASE_ = False   ,    SCREAMING_SNAKE_CASE_ = False   ,    SCREAMING_SNAKE_CASE_ = None   ,    SCREAMING_SNAKE_CASE_ = 0   ,    SCREAMING_SNAKE_CASE_ = None   ,    SCREAMING_SNAKE_CASE_ = None   ,    SCREAMING_SNAKE_CASE_ = None   ,    SCREAMING_SNAKE_CASE_ = False   ,    SCREAMING_SNAKE_CASE_ = False   ,    SCREAMING_SNAKE_CASE_ = False   ,    SCREAMING_SNAKE_CASE_ = False   ,    SCREAMING_SNAKE_CASE_ = True   ,    SCREAMING_SNAKE_CASE_ = None   ,    **SCREAMING_SNAKE_CASE_   ,    )    ->				BatchEncoding:
          # verify input
          if self.image_processor.apply_ocr and (boxes is not None):
              raise ValueError(
                  '''You cannot provide bounding boxes if you initialized the image processor with apply_ocr set to True.'''			)

          if self.image_processor.apply_ocr and (word_labels is not None):
              raise ValueError(
                  '''You cannot provide word labels if you initialized the image processor with apply_ocr set to True.'''			)

          if return_overflowing_tokens is True and return_offsets_mapping is False:
              raise ValueError('''You cannot return overflowing tokens without returning the offsets mapping.'''			)

          # first, apply the image processor
          UpperCamelCase	:str     							=       self.image_processor(images=SCREAMING_SNAKE_CASE_   ,    return_tensors=SCREAMING_SNAKE_CASE_			)

          # second, apply the tokenizer
          if text is not None and self.image_processor.apply_ocr and text_pair is None:
              if isinstance(SCREAMING_SNAKE_CASE_   ,    SCREAMING_SNAKE_CASE_			):
                  UpperCamelCase	:Union[str, Any]     							=       [text]  # add batch dimension (as the image processor always adds a batch dimension)
              UpperCamelCase	:Optional[int]     							=       features['''words''']

          UpperCamelCase	:Any     							=       self.tokenizer(
              text=text if text is not None else features['''words''']   ,    text_pair=text_pair if text_pair is not None else None   ,    boxes=boxes if boxes is not None else features['''boxes''']   ,    word_labels=SCREAMING_SNAKE_CASE_   ,    add_special_tokens=SCREAMING_SNAKE_CASE_   ,    padding=SCREAMING_SNAKE_CASE_   ,    truncation=SCREAMING_SNAKE_CASE_   ,    max_length=SCREAMING_SNAKE_CASE_   ,    stride=SCREAMING_SNAKE_CASE_   ,    pad_to_multiple_of=SCREAMING_SNAKE_CASE_   ,    return_token_type_ids=SCREAMING_SNAKE_CASE_   ,    return_attention_mask=SCREAMING_SNAKE_CASE_   ,    return_overflowing_tokens=SCREAMING_SNAKE_CASE_   ,    return_special_tokens_mask=SCREAMING_SNAKE_CASE_   ,    return_offsets_mapping=SCREAMING_SNAKE_CASE_   ,    return_length=SCREAMING_SNAKE_CASE_   ,    verbose=SCREAMING_SNAKE_CASE_   ,    return_tensors=SCREAMING_SNAKE_CASE_   ,    **SCREAMING_SNAKE_CASE_   ,    )

          # add pixel values
          UpperCamelCase	:Tuple     							=       features.pop('''pixel_values'''			)
          if return_overflowing_tokens is True:
              UpperCamelCase	:Union[str, Any]     							=       self.get_overflowing_images(SCREAMING_SNAKE_CASE_   ,    encoded_inputs['''overflow_to_sample_mapping''']			)
          UpperCamelCase	:Any     							=       images

          return encoded_inputs
      def    UpperCAmelCase						(    self   ,    SCREAMING_SNAKE_CASE_   ,    SCREAMING_SNAKE_CASE_			)    ->				Optional[Any]:
          # in case there's an overflow, ensure each `input_ids` sample is mapped to its corresponding image
          UpperCamelCase	:Dict     							=       []
          for sample_idx in overflow_to_sample_mapping:
              images_with_overflow.append(images[sample_idx]			)

          if len(SCREAMING_SNAKE_CASE_			) != len(SCREAMING_SNAKE_CASE_			):
              raise ValueError(
                  '''Expected length of images to be the same as the length of `overflow_to_sample_mapping`, but got'''
                  F''' {len(SCREAMING_SNAKE_CASE_			)} and {len(SCREAMING_SNAKE_CASE_			)}'''			)

          return images_with_overflow
      def    UpperCAmelCase						(    self   ,    *SCREAMING_SNAKE_CASE_   ,    **SCREAMING_SNAKE_CASE_			)    ->				List[Any]:
          return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE_   ,    **SCREAMING_SNAKE_CASE_			)
      def    UpperCAmelCase						(    self   ,    *SCREAMING_SNAKE_CASE_   ,    **SCREAMING_SNAKE_CASE_			)    ->				List[Any]:
          return self.tokenizer.decode(*SCREAMING_SNAKE_CASE_   ,    **SCREAMING_SNAKE_CASE_			)
      @property
      def    UpperCAmelCase						(    self			)    ->				Dict:
          return ["input_ids", "bbox", "token_type_ids", "attention_mask", "image"]
      @property
      def    UpperCAmelCase						(    self			)    ->				Union[str, Any]:
          warnings.warn(
              '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''   ,    SCREAMING_SNAKE_CASE_   ,    )
          return self.image_processor_class




      @property
      def    UpperCAmelCase						(    self			)    ->				Any:
          warnings.warn(
              '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''   ,    SCREAMING_SNAKE_CASE_   ,    )
          return self.image_processor













def   _A       (    SCREAMING_SNAKE_CASE__  :     float					,  SCREAMING_SNAKE_CASE__  :     float					,  SCREAMING_SNAKE_CASE__  :     float	):
    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'''	)

    UpperCamelCase	:Tuple     							=       value * saturation
    UpperCamelCase	:Any     							=       hue / 60
    UpperCamelCase	:Any     							=       chroma * (1 - abs(hue_section % 2 - 1	))
    UpperCamelCase	:Optional[int]     							=       value - chroma

    if hue_section >= 0 and hue_section <= 1:
        UpperCamelCase	:Any     							=       round(255 * (chroma + match_value)	)
        UpperCamelCase	:Union[str, Any]     							=       round(255 * (second_largest_component + match_value)	)
        UpperCamelCase	:List[str]     							=       round(255 * (match_value)	)
    elif hue_section > 1 and hue_section <= 2:
        UpperCamelCase	:Dict     							=       round(255 * (second_largest_component + match_value)	)
        UpperCamelCase	:Dict     							=       round(255 * (chroma + match_value)	)
        UpperCamelCase	:str     							=       round(255 * (match_value)	)
    elif hue_section > 2 and hue_section <= 3:
        UpperCamelCase	:Any     							=       round(255 * (match_value)	)
        UpperCamelCase	:Optional[Any]     							=       round(255 * (chroma + match_value)	)
        UpperCamelCase	:Union[str, Any]     							=       round(255 * (second_largest_component + match_value)	)
    elif hue_section > 3 and hue_section <= 4:
        UpperCamelCase	:Tuple     							=       round(255 * (match_value)	)
        UpperCamelCase	:Optional[Any]     							=       round(255 * (second_largest_component + match_value)	)
        UpperCamelCase	:str     							=       round(255 * (chroma + match_value)	)
    elif hue_section > 4 and hue_section <= 5:
        UpperCamelCase	:int     							=       round(255 * (second_largest_component + match_value)	)
        UpperCamelCase	:str     							=       round(255 * (match_value)	)
        UpperCamelCase	:List[str]     							=       round(255 * (chroma + match_value)	)
    else:
        UpperCamelCase	:Union[str, Any]     							=       round(255 * (chroma + match_value)	)
        UpperCamelCase	:List[str]     							=       round(255 * (match_value)	)
        UpperCamelCase	:Optional[int]     							=       round(255 * (second_largest_component + match_value)	)

    return [red, green, blue]


def   _A       (    SCREAMING_SNAKE_CASE__  :     int					,  SCREAMING_SNAKE_CASE__  :     int					,  SCREAMING_SNAKE_CASE__  :     int	):
    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'''	)

    UpperCamelCase	:str     							=       red / 255
    UpperCamelCase	:List[str]     							=       green / 255
    UpperCamelCase	:int     							=       blue / 255
    UpperCamelCase	:Optional[int]     							=       max(SCREAMING_SNAKE_CASE__					,  SCREAMING_SNAKE_CASE__					,  SCREAMING_SNAKE_CASE__	)
    UpperCamelCase	:int     							=       value - min(SCREAMING_SNAKE_CASE__					,  SCREAMING_SNAKE_CASE__					,  SCREAMING_SNAKE_CASE__	)
    UpperCamelCase	:Dict     							=       0 if value == 0 else chroma / value

    if chroma == 0:
        UpperCamelCase	:Dict     							=       0.0
    elif value == float_red:
        UpperCamelCase	:Optional[Any]     							=       60 * (0 + (float_green - float_blue) / chroma)
    elif value == float_green:
        UpperCamelCase	:List[str]     							=       60 * (2 + (float_blue - float_red) / chroma)
    else:
        UpperCamelCase	:str     							=       60 * (4 + (float_red - float_green) / chroma)

    UpperCamelCase	:int     							=       (hue + 360) % 360

    return [hue, saturation, value]



def   _A       (    SCREAMING_SNAKE_CASE__  :     list[float]					,  SCREAMING_SNAKE_CASE__  :     list[float]	):
    UpperCamelCase	:str     							=       abs(hsv_a[0] - hsv_a[0]	) < 0.2
    UpperCamelCase	:List[str]     							=       abs(hsv_a[1] - hsv_a[1]	) < 0.0_02
    UpperCamelCase	:Any     							=       abs(hsv_a[2] - hsv_a[2]	) < 0.0_02

    return check_hue and check_saturation and check_value





