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zero123plus

zero123plus

Guides Zero123Plus generation, ControlNet variants, demo launch, and Cog deployment workflows for single-image-to-multiview inference.

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Documentation de la Skill

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name: zero123plus description: "Guides Zero123Plus generation, ControlNet variants, demo launch, and Cog deployment workflows for single-image-to-multiview inference." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Zero123Plus

Use this skill when the task mentions Zero123Plus, single-image-to-multiview inference, depth ControlNet, normal generation, matting cleanup, Streamlit, Gradio, Docker/Gitpod, or Cog/Replicate deployment.

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Installation summary

This repository is GPU-first. The verified inspection stack used Python 3.11 and CUDA-capable PyTorch.

A representative setup is:

  1. Create a private Python 3.11 environment.
  2. Install a CUDA wheel for PyTorch and torchvision.
  3. Install the repo runtime stack summarized in references/dependency-and-runtime.md.
  4. Run python scripts/check_zero123plus_env.py --check-only or --require-cuda before a real generation run.

If you only need the generation path, start with the generation sub-skill. If you need local demos or deployment, start with the deployment sub-skill.

Minimal checks

  • python scripts/check_zero123plus_env.py --check-only
  • python scripts/check_zero123plus_env.py --require-cuda

Notes

  • The model weights are non-commercial even though the code is Apache 2.0.
  • CUDA is required for actual generation; CPU is not a full substitute.
  • Bundled scripts default to local-only loading and require --allow-download before they fetch missing model weights.
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