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name: rendering-evaluation description: "Guides gaussian-splatting rendering, metrics, pretrained-model evaluation, and output validation." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Rendering and Evaluation

Use this sub-skill when the task is to render a trained model, compute metrics, evaluate pretrained outputs, or understand the output layout produced by render.py, metrics.py, or full_eval.py.

Read First

• Read references/rendering-workflows.md for the standard render and pretrained-model flows.
• Read references/evaluation-workflows.md for paper-style benchmark orchestration and safe skip decisions.
• Read references/cli-reference.md for verified render.py, metrics.py, and full_eval.py flags.
• Read references/troubleshooting.md for model-layout, LPIPS, config-merge, and benchmark failures.
• Run scripts/validate_model_outputs.py when checking whether a model directory is ready for rendering or metrics.

What This Sub-Skill Covers

• Rendering a trained model into train/test PNG outputs.
• Computing PSNR, SSIM, and LPIPS from saved renders.
• Evaluating pretrained models by pointing render.py back to the source dataset with -s.
• Interpreting cfg_args merge behavior and output directory conventions.
• Understanding when full_eval.py is too expensive to run and how to construct the command instead.

What This Sub-Skill Excludes

• Training and checkpoint management. Route those to ../training/SKILL.md.
• Raw image conversion and depth preparation. Route those to ../data-preparation/SKILL.md.
• SIBR viewer build/run details. Route those to ../viewers/SKILL.md.
• CUDA installation and extension build errors. Route those to ../setup-and-backends/SKILL.md.

Typical Flow

1. Verify the model folder with the bundled validator.
2. Render train/test splits with render.py.
3. Inspect the PNG directories.
4. Run metrics.py if the GT/render layout is present.
5. Use full_eval.py only when the user explicitly wants the full benchmark orchestration.

Output Expectations

A future agent should be able to answer:

• Is this model directory ready to render?
• Which render.py flags should be used for a pretrained model?
• Why did metrics fail to find the output layout?
• What does full_eval.py expect as input, and when should it be skipped?