class_docstr: Constructs a Idefics image processor.
  
  Args:
      image_size (`int`, *optional*, defaults to 224):
          Resize to image size
      image_mean (`float` or `List[float]`, *optional*, defaults to `IDEFICS_STANDARD_MEAN`):
          Mean to use if normalizing the image. This is a float or list of floats the length of the number of
          channels in the image. Can be overridden by the `image_mean` parameter in the `preprocess` method. Can be
          overridden by the `image_mean` parameter in the `preprocess` method.
      image_std (`float` or `List[float]`, *optional*, defaults to `IDEFICS_STANDARD_STD`):
          Standard deviation to use if normalizing the image. This is a float or list of floats the length of the
          number of channels in the image. Can be overridden by the `image_std` parameter in the `preprocess` method.
          Can be overridden by the `image_std` parameter in the `preprocess` method.
      image_num_channels (`int`, *optional*, defaults to 3):
          Number of image channels.
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code: def __init__(
      self,
      image_size: int = 224,
      image_mean: Optional[Union[float, List[float]]] = None,
      image_std: Optional[Union[float, List[float]]] = None,
      image_num_channels: Optional[int] = 3,
      **kwargs,
  ) -> None:
      super().__init__(**kwargs)
  
      self.image_size = image_size
      self.image_num_channels = image_num_channels
      self.image_mean = image_mean
      self.image_std = image_std
  
file_path: transformers/src/transformers/models/idefics/image_processing_idefics.py
imports: from typing import Callable, Dict, List, Optional, Union
  from PIL import Image
  from ...image_processing_utils import BaseImageProcessor, BatchFeature
  from ...image_transforms import 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_torch_available
label_desc: Use image node_id 1 to create a new IdeficsImageProcessor object from inherited base classes: BaseImageProcessor with example: obj = IdeficsImageProcessor(image_size, image_mean, image_std, image_num_channels)