diff --git a/README.md b/README.md index 2b2203373..95ba60a48 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@

- + Documentation Status diff --git a/docs/developer_guides/viewer/local_viewer.md b/docs/developer_guides/viewer/local_viewer.md index 2931f8c0d..ef8b1ac1f 100644 --- a/docs/developer_guides/viewer/local_viewer.md +++ b/docs/developer_guides/viewer/local_viewer.md @@ -1,4 +1,8 @@ -# Local Server +# (Legacy Viewer) Local Server + +**Note:** this doc only applies to the legacy version of the viewer, which was the default in in Nerfstudio versions `<=0.3.4`. It was deprecated starting Nerfstudio version `1.0.0`, where it needs to be opted into via the `--vis viewer_legacy` argument. + +--- If you are unable to connect to `https://viewer.nerf.studio`, want to use Safari, or want to develop the viewer codebase, you can launch your own local viewer. diff --git a/nerfstudio/models/splatfacto.py b/nerfstudio/models/splatfacto.py index b23eabe00..a826599f9 100644 --- a/nerfstudio/models/splatfacto.py +++ b/nerfstudio/models/splatfacto.py @@ -155,6 +155,8 @@ class SplatfactoModelConfig(ModelConfig): """threshold of ratio of gaussian max to min scale before applying regularization loss from the PhysGaussian paper """ + output_depth_during_training: bool = False + """If True, output depth during training. Otherwise, only output depth during evaluation.""" class SplatfactoModel(Model): @@ -667,7 +669,10 @@ class SplatfactoModel(Model): if self.crop_box is not None and not self.training: crop_ids = self.crop_box.within(self.means).squeeze() if crop_ids.sum() == 0: - return {"rgb": background.repeat(int(camera.height.item()), int(camera.width.item()), 1)} + rgb = background.repeat(int(camera.height.item()), int(camera.width.item()), 1) + depth = background.new_ones(*rgb.shape[:2], 1) * 10 + accumulation = background.new_zeros(*rgb.shape[:2], 1) + return {"rgb": rgb, "depth": depth, "accumulation": accumulation} else: crop_ids = None camera_downscale = self._get_downscale_factor() @@ -732,7 +737,10 @@ class SplatfactoModel(Model): tile_bounds, ) # type: ignore if (self.radii).sum() == 0: - return {"rgb": background.repeat(int(camera.height.item()), int(camera.width.item()), 1)} + rgb = background.repeat(int(camera.height.item()), int(camera.width.item()), 1) + depth = background.new_ones(*rgb.shape[:2], 1) * 10 + accumulation = background.new_zeros(*rgb.shape[:2], 1) + return {"rgb": rgb, "depth": depth, "accumulation": accumulation} # Important to allow xys grads to populate properly if self.training: @@ -766,7 +774,7 @@ class SplatfactoModel(Model): alpha = alpha[..., None] rgb = torch.clamp(rgb, max=1.0) # type: ignore depth_im = None - if not self.training: + if self.config.output_depth_during_training or not self.training: depth_im = rasterize_gaussians( # type: ignore self.xys, depths,