ComfyUI-HunyuanPortrait is now available in ComfyUI, HunyuanPortrait is a diffusion-based condition control method that employs implicit representations for highly controllable and lifelike portrait animation.
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Make sure you have ComfyUI installed
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Clone this repository into your ComfyUI's custom_nodes directory:
cd ComfyUI/custom_nodes
git clone https://github.com/Yuan-ManX/ComfyUI-HunyuanPortrait.git
- Install dependencies:
cd ComfyUI-HunyuanPortrait
pip install torch torchvision torchaudio
pip install -r requirements.txt
All the weights should be placed under the ComfyUI/models/HunyuanPortrait/pretrained_weights direcotry. You can download weights manually as follows:
All models are stored in pretrained_weights by default:
pip install "huggingface_hub[cli]"
cd pretrained_weights
huggingface-cli download --resume-download stabilityai/stable-video-diffusion-img2vid-xt --local-dir . --include "*.json"
wget -c https://huggingface.co/LeonJoe13/Sonic/resolve/main/yoloface_v5m.pt
wget -c https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt/resolve/main/vae/diffusion_pytorch_model.fp16.safetensors -P vae
wget -c https://huggingface.co/FoivosPar/Arc2Face/resolve/da2f1e9aa3954dad093213acfc9ae75a68da6ffd/arcface.onnx
huggingface-cli download --resume-download tencent/HunyuanPortrait --local-dir hyportraitAnd the file structure is as follows:
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├── arcface.onnx
├── hyportrait
│ ├── dino.pth
│ ├── expression.pth
│ ├── headpose.pth
│ ├── image_proj.pth
│ ├── motion_proj.pth
│ ├── pose_guider.pth
│ └── unet.pth
├── scheduler
│ └── scheduler_config.json
├── unet
│ └── config.json
├── vae
│ ├── config.json
│ └── diffusion_pytorch_model.fp16.safetensors
└── yoloface_v5m.pt-
An NVIDIA 3090 GPU with CUDA support is required.
- The model is tested on a single 24G GPU.
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Tested operating system: Linux