def __call__(self, output, *args, **kwargs):
        """Parses the model output.

        Args:
            output: a batch of predictions ``output = Dict[Tensor]``,
                where the dict has the following keys:

                -   out (``FloatTensor[N, M, H, W]``): the segmentation map
                    probabilities for the ``N`` images across the ``M`` classes
            *args: unused arguments
            **kwargs: unused keyword arguments

        Returns:
            a list of :class:`fiftyone.core.labels.Segmentation` instances
        """
        probs = output["out"].detach().cpu().numpy()
        masks = probs.argmax(axis=1)
        return [fol.Segmentation(mask=mask) for mask in masks]
Parses the model output.

        Args:
            output: a batch of predictions ``output = Dict[Tensor]``,
                where the dict has the following keys:

                -   out (``FloatTensor[N, M, H, W]``): the segmentation map
                    probabilities for the ``N`` images across the ``M`` classes
            *args: unused arguments
            **kwargs: unused keyword arguments

        Returns:
            a list of :class:`fiftyone.core.labels.Segmentation` instances
        
fiftyone/utils/torch.py