https://github.com/TMElyralab/Comfyui-MusePose
https://github.com/TMElyralab/Comfyui-MusePose
Last synced: 4 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/TMElyralab/Comfyui-MusePose
- Owner: TMElyralab
- License: other
- Created: 2024-05-31T08:21:26.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-06-08T03:32:21.000Z (10 months ago)
- Last Synced: 2024-06-08T16:03:05.630Z (10 months ago)
- Language: Python
- Size: 3.44 MB
- Stars: 219
- Watchers: 2
- Forks: 20
- Open Issues: 26
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-comfyui - **Comfyui-MusePose** - to-video generation framework for virtual human under control signal such as pose. (All Workflows Sorted by GitHub Stars)
README
### MusePose
[MusePose](https://github.com/TMElyralab/MusePose) is an image-to-video generation framework for virtual human under control signal such as pose.
`MusePose` is the last building block of **the Muse opensource serie**. Together with [MuseV](https://github.com/TMElyralab/MuseV) and [MuseTalk](https://github.com/TMElyralab/MuseTalk), we hope the community can join us and march towards the vision where a virtual human can be generated end2end with native ability of full body movement and interaction. Please stay tuned for our next milestone!
### Comfyui-MusePose
If you're running on Linux, or non-admin account on windows you'll want to ensure `/ComfyUI/custom_nodes` and `Comfyui-MusePose` has write permissions.
Followed ComfyUI's manual installation steps and do the following:
- Navigate to your `/ComfyUI/custom_nodes/` folder
- Run `git clone https://github.com/TMElyralab/Comfyui-MusePose.git`
- Navigate to your `/ComfyUI/custom_nodes/Comfyui-MusePose` folder and run
```shell
pip install -r requirements.txt
pip install --no-cache-dir -U openmim
mim install mmengine
mim install "mmcv>=2.0.1"
mim install "mmdet>=3.1.0"
mim install "mmpose>=1.1.0"
```
- Start ComfyUI
#### Updates
- requirements.txt: diffusers 0.27.2 is now supported
### Download weights
You can download weights manually as follows:
1. Download our trained [weights](https://huggingface.co/TMElyralab/MusePose).
2. Download the weights of other components:
- [sd-image-variations-diffusers](https://huggingface.co/lambdalabs/sd-image-variations-diffusers/tree/main/unet)
- [sd-vae-ft-mse](https://huggingface.co/stabilityai/sd-vae-ft-mse)
- [dwpose](https://huggingface.co/yzd-v/DWPose/tree/main)
- [yolox](https://download.openmmlab.com/mmdetection/v2.0/yolox/yolox_l_8x8_300e_coco/yolox_l_8x8_300e_coco_20211126_140236-d3bd2b23.pth) - Make sure to rename to `yolox_l_8x8_300e_coco.pth`
- [image_encoder](https://huggingface.co/lambdalabs/sd-image-variations-diffusers/tree/main/image_encoder)
Finally, these weights should be organized in `pretrained_weights` as follows:
```
./pretrained_weights/
|-- MusePose
| |-- denoising_unet.pth
| |-- motion_module.pth
| |-- pose_guider.pth
| └── reference_unet.pth
|-- dwpose
| |-- dw-ll_ucoco_384.pth
| └── yolox_l_8x8_300e_coco.pth
|-- sd-image-variations-diffusers
| └── unet
| |-- config.json
| └── diffusion_pytorch_model.bin
|-- image_encoder
| |-- config.json
| └── pytorch_model.bin
└── sd-vae-ft-mse
|-- config.json
└── diffusion_pytorch_model.bin
```
### workflow demo
https://github.com/TMElyralab/Comfyui-MusePose/blob/main/musepose-workflow-demo.json
https://github.com/TMElyralab/Comfyui-MusePose/assets/114042542/9cd8b9b8-6876-4281-b7a0-a7fbcb2de7e1