OpenPifpaf pretrained data

Nobody has claimed this yet.

Hi,
As mentioned in the paper [https://arxiv.org/abs/2302.05543](url):

> Human Pose (OpenPifPaf) We use learning-based pose estimation method [27] to “find” humans
> from internet using a simple rule: an image with human must have at least 30% of the key points
> of the whole body detected. We obtain 80k pose-image-caption pairs. Note that we directly use
> visualized pose images with human skeletons as training condition. The model is trained with 400
> GPU-hours on Nvidia RTX 3090TI. The base model is Stable Diffusion 2.1. (See also Fig. 8.)

you have trained the SD2.1 on openpifpaf whole body and that is fascinating!

But i was wondering why there are no pretrained model or demo for openpifpof wholebody in the github page nor in the @huggingface !

Are you plan to release the model?
No matter how accurate it is, we all wanted to use it.
@lllyasviel @williamyang1991 @scarbain @eltociear @camenduru @sethupavan12

I also found some other people asking about it in issues but no answer!
@anwoflow @LCorleone @Olwaro @huytuong010101 @Paludgus @BlueAccords @ninjasaid2k @sALTaccount @richard-schwab @richard-schwab @TheLukaDragar

Thanks
Best regards

The issue asks whether the OpenPifPaf whole-body pretrained model or demo described in the linked paper will be released. Start by reading the paper reference and checking the existing ControlNet and Hugging Face resources; no files or tests are identified. Done would require a maintainer decision and, if approved, a model or demo release.

Written by the indexing model from the issue text.