def METHOD_NAME(self, image_uris: List[str], label_uri: str) -> None:
    """Generate predictions for the given image.
    Args:
        image_uris: URIs of the images to make predictions against.
            This can be any type of URI readable by Raster Vision
            FileSystems.
        label_uri: URI to save labels off into
    """
    if self.pipeline is None:
        self.scene.raster_source.uris = image_uris
        self.pipeline = self.config.build(self.tmp_dir)
        if not hasattr(self.pipeline, 'predict'):
            raise Exception(
                'pipeline in model bundle must have predict method')
    self.scene.raster_source.uris = image_uris
    self.scene.label_store.uri = label_uri
    if isinstance(self.scene.label_store,
                  SemanticSegmentationLabelStoreConfig):
        # create vector outputs for each class
        self.scene.label_store.vector_output = [
            PolygonVectorOutputConfig(class_id=i)
            for i, _ in enumerate(self.config.dataset.class_config.names)
        ]
    try:
        if self.update_stats:
            self.pipeline.analyze()
        self.pipeline.METHOD_NAME()
    except ChannelOrderError:
        raise ValueError(
            'The predict package is using a channel_order '
            'with channels unavailable in the imagery.\nTo set a new '
            'channel_order that only uses channels available in the '
            'imagery, use the --channel-order option.')