_resize` is set to `True`.
            resample (`PILImageResampling`, *optional*, defaults to `self.resample`):
                The resampling filter to use when resizing the input. Only has an effect if `do_resize` is set to
                `True`.
            do_center_crop (`bool`, *optional*, defaults to `self.do_center_crop`):
                Whether or not to center crop the input. If `True`, will center crop the input to the size specified by
                `crop_size`.
            crop_size (`Dict[str, int]`, *optional*, defaults to `self.crop_size`):
                The size to center crop the input to. Only has an effect if `do_center_crop` is set to `True`.
            do_rescale (`bool`, *optional*, defaults to `self.do_rescale`):
                Whether or not to rescale the input. If `True`, will rescale the input by dividing it by
                `rescale_factor`.
            rescale_factor (`float`, *optional*, defaults to `self.rescale_factor`):
                The factor to rescale the input by. Only has an effect if `do_rescale` is set to `True`.
            do_normalize (`bool`, *optional*, defaults to `self.do_normalize`):
                Whether or not to normalize the input. If `True`, will normalize the input by subtracting `image_mean`
                and dividing by `image_std`.
            image_mean (`Union[float, List[float]]`, *optional*, defaults to `self.image_mean`):
                The mean to subtract from the input when normalizing. Only has an effect if `do_normalize` is set to
                `True`.
            image_std (`Union[float, List[float]]`, *optional*, defaults to `self.image_std`):
                The standard deviation to divide the input by when normalizing. Only has an effect if `do_normalize` is
                set to `True`.
            return_tensors (`str` or `TensorType`, *optional*):
                The type of tensors to return. Can be one of:
                - Unset: Return a list of `np.ndarray`.
                - `TensorType.TENSORFLOW` or `'tf'`: Return a batch of type `tf.Tensor`.
                - `TensorType.PYTORCH` or `'pt'`: Return a batch of type `torch.Tensor`.
                - `TensorType.NUMPY` or `'np'`: Return a batch of type `np.ndarray`.
                - `TensorType.JAX` or `'jax'`: Return a batch of type `jax.numpy.ndarray`.
            data_format (`ChannelDimension` or `str`, *optional*, defaults to `ChannelDimension.FIRST`):
                The channel dimension format for the output image. Can be one of:
                - `ChannelDimension.FIRST`: image in (num_channels, height, width) format.
                - `ChannelDimension.LAST`: image in (height, width, num_channels) format.
                - Unset: defaults to the channel dimension format of the input image.
        Nz9Size and max_size must be specified if do_resize is True.z6Crop size must be specified if do_center_crop is True.z7Rescale factor must be specified if do_rescale is True.z=Image mean and std must be specified if do_normalize is True.zkInvalid image type. Must be of type PIL.Image.Image, numpy.ndarray, torch.Tensor, tf.Tensor or jax.ndarray.c