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shape-generation

shape-generation

Operate Hunyuan3D-2 image-to-shape, multiview, turbo, FlashVDM, and mesh export workflows.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentación de la Skill

GitHub

name: shape-generation description: "Operate Hunyuan3D-2 image-to-shape, multiview, turbo, FlashVDM, and mesh export workflows." metadata: disco-role: operating disable-model-invocation: true license: NOASSERTION

Hunyuan3D-2 Shape Generation

Use this sub-skill when the task is about Hunyuan3D-DiT geometry generation: single-image to mesh, multiview to mesh, mini/fast/turbo model variants, FlashVDM, seeds, octree settings, output formats, or VAE/latent shape workflows.

Route here for

  • Loading hy3dgen.shapegen.Hunyuan3DDiTFlowMatchingPipeline and generating a trimesh mesh.
  • Choosing among tencent/Hunyuan3D-2, tencent/Hunyuan3D-2mini, tencent/Hunyuan3D-2mv, and Hunyuan3D-2.1-compatible subfolders.
  • Multiview image dictionaries with front, back, left, and right keys.
  • Turbo or FlashVDM decoding and mc_algo, octree_resolution, num_chunks, guidance_scale, seed, and export troubleshooting.
  • Shape postprocessors such as floater removal, degenerate-face cleanup, and face reduction when used before export or texturing.

Do not route here for

  • Texture synthesis and custom rasterizer details: use ../texture-and-mesh/.
  • FastAPI, Gradio, Blender, or client payload work: use ../services-and-integrations/.
  • Installation, CUDA extension build order, and model cache planning: use ../environment-and-model-setup/.

Essential references

  • API reference for constructor/call signatures, parameter meanings, model presets, and postprocessors.
  • Workflows for single-image, multiview, turbo/FlashVDM, VAE, and export recipes.
  • Troubleshooting for CUDA/model-cache/background-removal/export failures.

Bundled helper

  • scripts/generate_shape.py provides a safe CLI wrapper with --dry-run and lazy heavy imports. Use it to prepare or run shape generation without depending on the original repository examples.

Example dry-run:

python scripts/generate_shape.py --preset base --image input.png --output mesh.glb --dry-run
python scripts/generate_shape.py --preset mv --view front=front.png --view left=left.png --output mesh.glb --dry-run

Actual generation requires a CUDA-capable Hunyuan3D environment and model weights. CPU-only imports or dry-runs are not proof that shape generation works.

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