---

name: reconstruction description: "Guides SplaTAM offline RGB-D SLAM, reconstruction config edits, evaluation, visualization, PLY export, post-SplaTAM optimization, and GT-pose Gaussian splatting workflows." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

Reconstruction Sub-Skill

Use this sub-skill for SplaTAM reconstruction and saved-output workflows: offline SLAM, benchmark configs, checkpoint resume, post-SplaTAM optimization, Gaussian splatting with GT poses, novel-view evaluation, final/online visualization, and PLY export.

Route iPhone/NeRFCapture streaming and dataset collection to ../capture/SKILL.md. Capture-produced datasets return here for offline SLAM once the dataset layout is valid.

Required preconditions

• A SplaTAM checkout root with the repo script/config layout.
• A CUDA-capable PyTorch runtime and importable diff_gaussian_rasterization.
• A dataset matching the chosen config family.
• W&B disabled or configured when using public benchmark configs that default to use_wandb=True.

Run the root environment gate before expensive reconstruction:

python scripts/check_env.py --require-cuda --require-rasterizer

Read root data/config guidance before editing dataset paths.

Workflow routing

Task	Entry point	Read
Run RGB-D SLAM/tracking/mapping on Replica, TUM, ScanNet, ScanNet++, Replica-V2, or iPhone dataset	python scripts/splatam.py <config.py>	references/workflows.md
Resume from saved checkpoint	scripts/splatam.py with load_checkpoint=True and checkpoint_time_idx	references/configuration.md
Export a completed run to PLY	python scripts/export_ply.py <config.py>	references/workflows.md
Validate a saved result before export/eval	Bundled sub-skills/reconstruction/scripts/check_result_bundle.py	references/workflows.md
Visualize reconstruction	python viz_scripts/final_recon.py <config.py> or python viz_scripts/online_recon.py <config.py>	references/workflows.md
Refine a SplaTAM checkpoint with post optimization	python scripts/post_splatam_opt.py <config.py>	references/workflows.md
Run Gaussian splatting from GT poses	python scripts/gaussian_splatting.py <config.py>	references/workflows.md
Train/test or novel-view evaluation	python scripts/eval_novel_view.py <config.py>	references/workflows.md

Safe operating sequence

1. Pick the closest public config family under the checkout's configs/ tree.
2. Copy the config to a working file before editing benchmark defaults.
3. Set dataset paths, frame range, run_name, and use_wandb deliberately.
4. For smoke checks, reduce frame count and iteration counts; do not infer benchmark quality from a reduced run.
5. Launch only after the root environment check passes.
6. Validate workdir/run_name/params.npz with the bundled result checker before export, visualization, or downstream reporting.
7. Use the nearest troubleshooting reference for failures:
   • root troubleshooting for install/import/data/W&B/Open3D issues.
   • references/troubleshooting.md for reconstruction-specific output, memory, config, or eval issues.

Bundled helper

Run this helper against a saved result directory:

python sub-skills/reconstruction/scripts/check_result_bundle.py \
  --result-dir <workdir>/<run_name> --require-params

It checks the shape and presence of key params.npz arrays without importing CUDA or opening a viewer.