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생산성 및 협업 · SKILL.md

splatam

splatam

Routes agents working with SplaTAM RGB-D SLAM, Gaussian-splat reconstruction, iPhone/NeRFCapture capture, evaluation, export, and troubleshooting workflows.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: splatam description: "Routes agents working with SplaTAM RGB-D SLAM, Gaussian-splat reconstruction, iPhone/NeRFCapture capture, evaluation, export, and troubleshooting workflows." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

SplaTAM Repo Skill

Use this repo skill when a task involves SplaTAM: dense RGB-D SLAM with 3D Gaussians, post-SplaTAM Gaussian-splat optimization, reconstruction evaluation/export/visualization, or iPhone/NeRFCapture live capture.

Fit and boundaries

Use this skill when the user asks to:

  • Prepare or repair a SplaTAM runtime environment.
  • Run, adapt, or debug SplaTAM reconstruction configs for Replica, Replica-V2, TUM RGB-D, ScanNet, ScanNet++, or iPhone/NeRFCapture data.
  • Export params.npz outputs to PLY splats or inspect/evaluate saved reconstructions.
  • Capture RGB-D frames from the NeRFCapture iOS app or run the live iPhone demo.

Avoid this skill when the task is generic 3D Gaussian Splatting unrelated to SplaTAM, pure dataset conversion with no SplaTAM config/output target, or paper-level reproduction without a SplaTAM checkout.

First checks

  1. Work from a SplaTAM checkout root that has the expected scripts/, configs/, datasets/, utils/, and viz_scripts/ layout.

  2. Read references/environment.md before installing or changing dependencies. SplaTAM is CUDA-first; CPU-only is not a supported substitute for the selected workflows.

  3. If you still need to set up the runtime, follow the baseline install in references/environment.md (conda create, conda install, then pip install -r requirements.txt) before any workflow-specific changes.

  4. Run the bundled environment check before expensive work:

    python scripts/check_env.py --require-cuda --require-rasterizer
    
  5. Read references/data-and-configs.md before editing Python config modules or relocating datasets.

  6. Read references/troubleshooting.md when imports, CUDA, dataset paths, W&B, Open3D, or the custom rasterizer fail.

Routing

User intentRouteRead next
Offline RGB-D SLAM, mapping/tracking config, checkpoints, export PLY, final/online visualization, post-SplaTAM optimization, GT-pose Gaussian splatting, novel-view evaluationsub-skills/reconstruction/sub-skills/reconstruction/SKILL.md
iPhone or LiDAR Apple device capture, NeRFCapture DDS streaming, online demo, capture-only dataset writing, capture-to-offline reconstructionsub-skills/capture/sub-skills/capture/SKILL.md
Cross-cutting install/backend/data/config failuresRoot referencesreferences/environment.md, references/troubleshooting.md

Core operating facts

  • Main scripts load a Python config file with SourceFileLoader and expect a module-level config dictionary.
  • Main reconstruction outputs are under config["workdir"] / config["run_name"], usually including a copied config.py, params.npz, evaluation image/metric folders, optional checkpoints, and optional splat.ply after export.
  • All primary reconstruction and live demo paths call CUDA tensors and diff_gaussian_rasterization; a working NVIDIA CUDA PyTorch stack is required.
  • Public configs set use_wandb=True for some benchmark presets. Disable or redirect W&B before local non-credentialed runs.
  • Bash capture wrappers adjust kernel UDP socket buffers with sudo sysctl; do not run them without explicit authorization. Prefer the Python capture entry points when avoiding system mutation.

Bundled helpers

  • scripts/check_env.py checks Python imports, torch/CUDA readiness, and the custom rasterizer without running a dataset.
  • sub-skills/reconstruction/scripts/check_result_bundle.py validates a saved reconstruction directory and params.npz schema before export/eval handoff.
  • sub-skills/capture/scripts/validate_nerfcapture_dataset.py validates a captured NeRFCapture dataset layout before using it in SplaTAM.

Provenance and refresh

Read references/repo-provenance.md before deciding whether this skill is current for a checkout. If the SplaTAM commit, dirty state, public configs, main scripts, dataset loaders, or dependency requirements changed materially, refresh this repo skill before relying on it.

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