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# gate_scenes_export
Self-contained bundle of two sagesplat scenes (left/right) plus the object
extractions in their shared (joint) mocap frame.
## Layout
```
gate_scenes_export/
├── README.md
├── MANIFEST.txt
├── left_scene/
│ ├── mocap_processed/ # data dir (referenced by config.yml as "./mocap_processed")
│ │ ├── images/ # 242 corrected RGB frames
│ │ ├── transforms.json # mocap-frame camera poses
│ │ └── sparse_pc.ply # initial point cloud (mocap frame)
│ └── mocap_outputs/sagesplat_mocap/sagesplat/2026-05-11_153901/
│ ├── config.yml # trainer config (data path is relative)
│ ├── dataparser_transforms.json # mocap → nerfstudio internal frame
│ └── nerfstudio_models/step-000029999.ckpt
├── right_scene/ # mirror layout
│ └── ... # training run timestamp 2026-05-11_144353
└── objects_final/
├── README.md # detailed transform usage
├── left_gate.ply, right_gate.ply # all PLYs in JOINT mocap frame
├── left_table.ply, right_table.ply
├── joint_mocap_to_nerf.json # the transforms
├── objects_summary.json # per-object AABBs, plane, polygon
└── right_to_left_icp.json # ICP that built joint mocap
```
`config.yml` stores the data path as the **relative** string `mocap_processed`,
so ns-viewer/ns-eval/ns-render must be launched with the scene directory as
`cwd`. Everything else (checkpoint, dataparser transform) is referenced as
a path relative to the run timestamp directory.
## Environment
This bundle was produced with the conda env `sagesplat` at
`/home/javier/miniconda3/envs/sagesplat`. To reproduce on another host:
- python 3.10
- pytorch 2.1.2 + cu118
- nerfstudio 1.1.5
- gsplat 1.4.0
- tinycudann (built against the same CUDA toolkit)
- sagesplat (editable install from
[Splat-MOVER](https://github.com/StanfordMSL/Splat-MOVER))
- runtime env knobs we use on this machine:
- `PYTHONNOUSERSITE=1` (so `~/.local/lib/python3.10/site-packages` doesn't
shadow the conda env)
- `QT_QPA_PLATFORM=offscreen` (only relevant when running headless)
- `CUDA_HOME` set to a conda env that ships a full CUDA toolkit, with
`LIBRARY_PATH` extended with that env's stubs+system libcuda
## Launching `ns-viewer` for a scene
```bash
# left
cd gate_scenes_export/left_scene
ns-viewer --load-config mocap_outputs/sagesplat_mocap/sagesplat/2026-05-11_153901/config.yml
# right
cd gate_scenes_export/right_scene
ns-viewer --load-config mocap_outputs/sagesplat_mocap/sagesplat/2026-05-11_144353/config.yml
```
Viser will bind to `http://0.0.0.0:7007`. `ns-eval` / `ns-render` take the
same `--load-config` argument.
## Using the object point clouds
See `objects_final/README.md` for the full transform chain and copy-pastable
Python snippets. Short version:
- All PLYs in `objects_final/` are in the **joint mocap frame**:
z-up, origin at the ArUco tag, +x along the tag's printed +y direction.
- The right scene's PLYs have an ICP correction baked in so they
align with the left scene's mocap (the joint reference).
- `objects_final/joint_mocap_to_nerf.json` carries the per-scene 4×4
matrices needed to push points from joint mocap into either splat's
nerfstudio-internal frame (for use with `cv.aruco`-style PnP, or to
query the splat for renders at a specific mocap pose).
## Frame conventions, quick reference
| frame | origin | up | notes |
|---|---|---|---|
| joint mocap | ArUco tag center | +z | reference; equals left scene's mocap |
| left mocap | tag center | +z | identical to joint mocap |
| right mocap | tag center | +z | offset by ICP correction (≈70 mm xyz, -0.5° yaw) |
| left nerf-internal | shifted | +z (auto-oriented) | nerfstudio dataparser applied |
| right nerf-internal | shifted | +z (auto-oriented) | nerfstudio dataparser applied |
## Total size: ~12 GB
Per-component:
- `left_scene/` : 76 MB data + 4.9 GB checkpoint = ~5.0 GB
- `right_scene/` : 71 MB data + 6.3 GB checkpoint = ~6.4 GB
- `objects_final/` : 11 MB
`MANIFEST.txt` carries a build-time snapshot of the same.