Method output_to_point_clouds

point_e/diffusion/sampler.py:227–237

(self, output: torch.Tensor)

        return pos, aux

    def output_to_point_clouds(self, output: torch.Tensor) -> List[PointCloud]:
        res = []
        for sample in output:
            xyz, aux = self.split_model_output(sample[None], rescale_colors=True)
            res.append(
                PointCloud(
                    coords=xyz[0].t().cpu().numpy(),
                    channels={k: v[0].cpu().numpy() for k, v in aux.items()},
                )
            )
        return res

    def with_options(
        self,