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name: coarse-training description: "Build, tune, and troubleshoot Make-It-3D coarse-stage NeRF optimization commands for frontal and full-360 single-image 3D creation." metadata: disco-role: operating disable-model-invocation: true license: NO_LICENSE

Coarse Training

Use this sub-skill when a user wants to run or adapt the Make-It-3D coarse stage: the initial frontal-view optimization and the follow-up full 360-degree optimization. Use environment-and-inputs first if dependencies, DPT weights, Hugging Face cache, or the alpha input are not confirmed.

What This Sub-Skill Covers

• Constructing README-backed python main.py commands for the two coarse phases.
• Important CLI flags and defaults from main.py.
• Choosing --text, --guidance, --sd_version, --need_back, --fp16, --backbone, and camera ranges.
• Understanding coarse-stage outputs under results/<workspace>.
• Troubleshooting long/stretched geometry, missing captions, OOM, and default-backbone failures.

Refinement, test rendering, and mesh export are owned by refinement-and-export.

Required Reads and Scripts

• Read references/workflow.md for the two-stage run sequence and output expectations.
• Read references/cli-reference.md for flags, defaults, and source quirks.
• Read references/troubleshooting.md for geometry and training failures.
• Run scripts/build_training_commands.py to generate safe, copyable commands.

Command Construction Pattern

python /path/to/skill/sub-skills/coarse-training/scripts/build_training_commands.py \
  --workspace NAME \
  --ref-path REF_ALPHA.png \
  --text "a short object prompt"

The helper prints:

1. Frontal phase: --phi_range 135 225 --iters 2000.
2. Full-360 phase: --phi_range 0 360 --albedo_iters 3500 --iters 5000 --final.

By default it includes --text when provided so BLIP2 captioning is not triggered. Add --need-back for explicit back-view prompt conditioning, --fp16 if mixed precision is desired and supported, and --vanilla-backbone to emit --backbone vanilla when tiny-cuda-nn is unavailable and the user accepts slower training.

Operating Checklist

Before running the generated commands:

• Alpha image validated.
• DPT hybrid weights present at the expected path or source patched intentionally.
• CUDA torch allocation works.
• Raymarching extension can import/build in the active environment.
• tiny-cuda-nn installed unless --backbone vanilla is intentionally used.
• Stable Diffusion or CLIP guidance assets are available.
• Workspace name is unique or the user intentionally wants to resume/overwrite results/<workspace>.

After the frontal phase, inspect logs and intermediate renders before expanding to 360 degrees. After the full-360 phase with --final, expect test render output and optionally mesh save if --save_mesh is also set and export dependencies are installed.