src/transformers/models/layoutlmv3/image_processing_layoutlmv3.py/LayoutLMv3ImageProcessor/resize
class LayoutLMv3ImageProcessor:    def resize(
        self,
        image: np.ndarray,
        size: Dict[str, int],
        resample: PILImageResampling = PILImageResampling.BILINEAR,
        data_format: Optional[Union[str, ChannelDimension]] = None,
        **kwargs,
    ) -> np.ndarray:
        """
        Resize an image to (size["height"], size["width"]) dimensions.

        Args:
            image (`np.ndarray`):
                Image to resize.
            size (`Dict[str, int]`):
                Size of the output image.
            resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BILINEAR`):
                Resampling filter to use when resiizing the image.
            data_format (`str` or `ChannelDimension`, *optional*):
                The channel dimension format of the image. If not provided, it will be the same as the input image.
        """
        size = get_size_dict(size)
        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()}")
        output_size = (size["height"], size["width"])
        return resize(image, size=output_size, resample=resample, data_format=data_format, **kwargs)