def visualize(
        self,
        images: Union[Tensor, List[Tensor]],
        edge_maps: Optional[Union[Tensor, List[Tensor]]] = None,
        output_type: str = "torch",
    ) -> Union[Tensor, List[Tensor], List["Image.Image"]]:  # type: ignore
        """Draw the super resolution results.

        Args:
            images: input tensor.
            edge_maps: detected edges.
            output_type: type of the output.

        Returns:
            output tensor.

        """
        if edge_maps is None:
            edge_maps = self.forward(images)
        output = []
        for edge_map in edge_maps:
            output.append(edge_map)

        return self._tensor_to_type(output, output_type, is_batch=isinstance(images, Tensor))
Draw the super resolution results.

        Args:
            images: input tensor.
            edge_maps: detected edges.
            output_type: type of the output.

        Returns:
            output tensor.

        
kornia/models/super_resolution/base.py