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export-and-evaluation

export-and-evaluation

Export DreamCraft3D meshes, inspect output directories, and plan optional metrics or progress videos.

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Documentation de la Skill

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name: export-and-evaluation description: "Export DreamCraft3D meshes, inspect output directories, and plan optional metrics or progress videos." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Export and Evaluation

Use this sub-skill when a task is about exporting a trained DreamCraft3D result, finding checkpoints/configs, summarizing outputs/ or outputs-gradio/, diagnosing mesh-export failures, or planning optional CLIP/LPIPS/CX/PSNR metrics and progress videos.

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When to use this sub-skill

Use it for requests like:

  • "Export an OBJ from my DreamCraft3D checkpoint."
  • "Find the last.ckpt and parsed.yaml for a run."
  • "Why does mesh export fail in a headless Docker container?"
  • "Summarize what artifacts exist under this output directory."
  • "How do the optional metrics scripts expect inputs?"

Export protocol

  1. Confirm the texture or geometry trial has both configs/parsed.yaml and a compatible checkpoint such as ckpts/last.ckpt.
  2. Build the export command using launch.py --export, resume=<checkpoint>, and system.exporter_type=mesh-exporter.
  3. Expect actual export to require CUDA, the active DreamCraft3D environment, nvdiffrast, xatlas, and any checkpoint-specific model components.
  4. After export, inspect the generated export directory for OBJ/MTL/texture artifacts.

Safe output summary

python <skill-dir>/sub-skills/export-and-evaluation/scripts/summarize_outputs.py \
  --trial-dir outputs/dreamcraft3d-texture/<prompt-tag>@LAST --require-checkpoint --require-parsed-config

Use --json for structured output and --require-export when checking an already exported trial.

Route elsewhere

  • Four-stage training and checkpoint chaining before export: generation-pipeline.
  • Image input and sidecars: image-preparation.
  • LoRA/Zero123++ texture boosting: bootstrapped-texture.
  • Gradio live progress and Docker setup: interfaces-and-monitoring.
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