class MarigoldDepthOutput(BaseOutput):
    """
    Output class for Marigold monocular depth prediction pipeline.

    Args:
        prediction (`np.ndarray`, `torch.Tensor`):
            Predicted depth maps with values in the range [0, 1]. The shape is always $numimages \times 1 \times height
            \times width$, regardless of whether the images were passed as a 4D array or a list.
        uncertainty (`None`, `np.ndarray`, `torch.Tensor`):
            Uncertainty maps computed from the ensemble, with values in the range [0, 1]. The shape is $numimages
            \times 1 \times height \times width$.
        latent (`None`, `torch.Tensor`):
            Latent features corresponding to the predictions, compatible with the `latents` argument of the pipeline.
            The shape is $numimages * numensemble \times 4 \times latentheight \times latentwidth$.
    """

    prediction: Union[np.ndarray, torch.Tensor]
    uncertainty: Union[None, np.ndarray, torch.Tensor]
    latent: Union[None, torch.Tensor]
/Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/pipelines/marigold/pipeline_marigold_depth.py