1 rendering
rendering
Rendering utilities used by oracle RRI and rollout diagnostics.
Candidate renders are metric depth images generated from ASE/EFM meshes and candidate PoseTW cameras. PyTorch3D returns z-depth in the physical camera frame; unprojection converts valid pixels back into world-frame point clouds that can be joined with semidense history before point-mesh RRI scoring.
Rendering code is an oracle/evaluation dependency. Actor-visible datasets may store poses, masks, and selected diagnostics, but rendered GT-depth point clouds are supervision artifacts unless an experiment explicitly exposes them.
1.1 Classes
| Name | Description |
|---|---|
| CandidateDepthRenderer | High-level wrapper that renders depth for compact valid candidate poses. |
| CandidateDepths | Typed result for candidate depth rendering. |
| CandidatePointClouds | Batched candidate point clouds plus fused semi-dense reconstruction. |
| Efm3dDepthRenderer | CPU depth renderer built on trimesh ray tracing. |
| Efm3dDepthRendererConfig | Configuration for Efm3dDepthRenderer. |
| Pytorch3DDepthRenderer | Depth rendering backend based on PyTorch3D. |
| Pytorch3DDepthRendererConfig | Configuration for Pytorch3DDepthRenderer. |
1.2 Functions
| Name | Description |
|---|---|
| build_candidate_pointclouds | Convert stacked depth maps into batched point clouds and fuse with SLAM. |