README + CLAUDE.md previously claimed Hunyuan3D-2/ and docker/outputs/ were "gitignored". The repo has no .gitignore at all; those paths are just untracked. Use "untracked" / "not committed" wording instead so the operator contract (clone upstream, don't add) is clear without implying a gitignore safety net. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
1.7 KiB
1.7 KiB
Hunyuan3D-2 + Sunnie Animation Pipeline
Self-hosted Hunyuan3D-2 (mini-turbo variant) for generating a 3D Sunnie mesh from a reference image, then rigging and animating in Blender via Mixamo.
Requirements
- NVIDIA GPU with CUDA 12.4 support and ≥ 10 GB VRAM (tuned for RTX 3080).
- Docker + the NVIDIA Container Toolkit (
nvidiaruntime exposed to compose). - Network egress to pull PyTorch wheels + Hugging Face model weights on first build / first run.
Quick Start
# Clone the upstream model repo into this directory (not a submodule —
# the Dockerfile COPYs it via the build context). Operator-managed; not
# committed.
git clone https://github.com/Tencent-Hunyuan/Hunyuan3D-2.git
# Build and run
cd docker
docker compose build
docker compose up
# Gradio UI at http://localhost:8080
Project Structure
hunyuan3d-sunnie/
Hunyuan3D-2/ # cloned upstream — operator-managed, not committed
docker/
Dockerfile # custom build, CUDA 12.4, community-derived
compose.yml # GPU compose; pins mini-turbo + flashvdm + low_vram
outputs/ # generated .glb meshes land here (not committed)
Notes
- First run downloads model weights (~several GB) to the
hunyuan3d-modelsnamed volume — both the mini-turbo mesh model and the full Hunyuan3D-2 model for PBR texture generation. - Uses the
mini-turbovariant with--low_vram_modeand--enable_flashvdmfor the 10 GB VRAM ceiling on a 3080. Bigger card? Drop--low_vram_mode. Smaller card? Expect OOMs. - Outputs
.glbwith PBR textures, ready for Blender import → Mixamo rigging. - See
CLAUDE.mdfor the agent-facing gotchas (don't-touch flags, CUDA pin rationale, etc.).