utputs ([`OwlViTImageGuidedObjectDetectionOutput`]):
                Raw outputs of the model.
            threshold (`float`, *optional*, defaults to 0.0):
                Minimum confidence threshold to use to filter out predicted boxes.
            nms_threshold (`float`, *optional*, defaults to 0.3):
                IoU threshold for non-maximum suppression of overlapping boxes.
            target_sizes (`torch.Tensor`, *optional*):
                Tensor of shape (batch_size, 2) where each entry is the (height, width) of the corresponding image in
                the batch. If set, predicted normalized bounding boxes are rescaled to the target sizes. If left to
                None, predictions will not be unnormalized.

        Returns:
            `List[Dict]`: A list of dictionaries, each dictionary containing the scores, labels and boxes for an image
            in the batch as predicted by the model. All labels are set to None as
            `OwlViTForObjectDetection.image_guided_detection` perform one-shot object detection.
        rW