ComfyUI-MeshHamer

ComfyUI-MeshHamer

Installation

Before installation, you should install the CUDA_Toolkit first.

Enter to the ComfyUI root folder, run the following commands:

cd custom_nodes
git clone --recursive https://github.com/ader47/comfyui_meshhamer.git
cd comfyui_meshhamer
cd mesh_hamer
pip install -e .[all]
cd ./third-party/ViTPose
pip install -e .

Download models

I have uploaded the model files to the Huggingface. The checkpoints and model config files should be placed in the following structure:

- comfyui_meshhamer
    - mesh_hamer
      - __DATA
        - data
          - mano
              MANO_RIGHT.pkl
          - mano_mean_params.npz
        - hamer_ckpts
          - checkpoints
              hamer.ckpt
          dataset_config.yaml
          model_config.yaml
        - vitpose_ckpts
          - vitpose+_huge
            wholebody.pth
      model_final_f05665.pkl

Notice

This pipline needs about 10GB VRAM. If you have a GPU with less than 10GB VRAM, you can try to change DEVICE in the config.py file.

TODO

• Change the dectectron2 or ViTPose to reduce the VRAM usage.
• Add external detector api.

Acknowledgements

Parts of the code are borrowed from the following repositories:

• Hamer
• controlnet_aux
• HandRefiner