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name: evaluation-and-results description: "Evaluate MonoGS runs, inspect saved result trees, and handle W&B-safe metric workflows." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Evaluation and Results

Use this sub-skill when the user asks for MonoGS metrics, --eval, saved outputs, ATE/rendering scores, result folders, W&B behavior, or final Gaussian PLY artifacts.

Route away

• To choose a monocular/RGB-D/stereo run command before evaluation, use offline-slam.
• To validate dataset roots or YAML inheritance, use data-and-configs.
• To debug CUDA installation, extension imports, or Open3D dependencies, use environment-setup.
• To operate a RealSense camera or the live GUI, use live-demo.

Fast path

1. Confirm the SLAM command already works on the selected config; evaluation is not a substitute for environment or dataset setup.
2. Decide whether to use the built-in evaluation flag:
   • python slam.py --config <config> --eval forces save_results=True, use_gui=False, eval_rendering=True, and use_wandb=True.
   • If W&B login/network is not available, prefer WANDB_MODE=disabled python slam.py --config <config> --eval.
   • For a W&B-free custom evaluation, copy the config and set Results.save_results: true, Results.use_gui: false, Results.eval_rendering: true, and Results.use_wandb: false, then omit --eval.
3. After a run, inspect the timestamped result directory with scripts/summarize_results.py.
4. Read references/results-and-metrics.md before interpreting ATE, PSNR, SSIM, LPIPS, FPS, or PLY outputs.

Bundled references

• Evaluation workflows explains built-in --eval, W&B-safe modes, and evaluation commands.
• Results and metrics maps result-tree files to MonoGS evaluation code paths.
• Troubleshooting covers missing metrics, W&B prompts, LPIPS downloads, empty trajectories, and rendering failures.
• scripts/summarize_results.py summarizes a result root without importing the MonoGS checkout.