Sign in

Nodes Browser

ComfyDeploy: How ComfyUI-MagicDance works in ComfyUI?

What is ComfyUI-MagicDance?

ComfyUI supports over [a/Boese0601/MagicDance](https://github.com/Boese0601/MagicDance).

How to install it in ComfyDeploy?

Head over to the machine page

  1. Click on the "Create a new machine" button
  2. Select the Edit build steps
  3. Add a new step -> Custom Node
  4. Search for ComfyUI-MagicDance and select it
  5. Close the build step dialig and then click on the "Save" button to rebuild the machine

ComfyUI-MagicDance

ComfyUI supports over Boese0601/MagicDance, which generates a short video from a series of OpenPose images and a static reference image.

Installation

Assuming that you are under your ComfyUI root directory

git clone https://github.com/bombax-xiaoice/ComfyUI-MagicDance custom_nodes/ComfyUI-MagicDance

pip install -r custom_nodes/ComfyUI-MagicDance/requirements.txt

You can download the model file from huggingface or its mirror site beforehand, or just wait for the first run of (Down)Load MagicDance Model to download it

wget https://huggingface.co/Boese0601/MagicDance/resolve/main/model_state-110000.th -O custom_nodes/ComfyUI-MagicDance/pretrained_weights/model_state-110000.th

wget https://hf-mirror.com/Boese0601/MagicDance/resolve/main/model_state-110000.th -O custom_nodes/ComfyUI-MagicDance/pretrained_weights/model_state-110000.th

Example Workflow

Drag the following image into comfyui, or click Load for custom_nodes/ComfyUI-MagicDance/example_data/magicdance-comfy-example.json

Results run under comfy based on poses and image provided by MagicDance

https://github.com/user-attachments/assets/ef54fc3c-7b9b-49d5-a36f-3d6313ff88da

Tips

Allow multiple poses (pose images) but only one single reference (image encoded to latent). The input latents should set its first dimension the same as the number of poses, width and height set the same as the reference image.

Verified to work on a single NVidia RTX 3070 card with 8G graphics memory, where VAE encoder, TextEncoder, Transformer and VAE decoder are loaded seperately. If you have enough graphics memory. You can try use --highvram on comfy start, where the entire pipeline is loaded into GPU directly to spare unnecessary conversion between CPU and GPU.

It is recommend to choose a preview method (inside comfy Manager), so that you can see the progress of each pose and each sampler step during the long run.