src/transformers/models/efficientformer/image_processing_efficientformer.py/EfficientFormerImageProcessor/__init__
class EfficientFormerImageProcessor:    def __init__(
        self,
        do_resize: bool = True,
        size: Optional[Dict[str, int]] = None,
        resample: PILImageResampling = PILImageResampling.BICUBIC,
        do_center_crop: bool = True,
        do_rescale: bool = True,
        rescale_factor: Union[int, float] = 1 / 255,
        crop_size: Dict[str, int] = None,
        do_normalize: bool = True,
        image_mean: Optional[Union[float, List[float]]] = None,
        image_std: Optional[Union[float, List[float]]] = None,
        **kwargs,
    ) -> None:
        super().__init__(**kwargs)
        size = size if size is not None else {"height": 224, "width": 224}
        size = get_size_dict(size)
        crop_size = crop_size if crop_size is not None else {"height": 224, "width": 224}
        crop_size = get_size_dict(crop_size, default_to_square=True, param_name="crop_size")

        self.do_resize = do_resize
        self.do_rescale = do_rescale
        self.do_normalize = do_normalize
        self.do_center_crop = do_center_crop
        self.crop_size = crop_size
        self.size = size
        self.resample = resample
        self.rescale_factor = rescale_factor
        self.image_mean = image_mean if image_mean is not None else IMAGENET_DEFAULT_MEAN
        self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD