An implementation of the method in CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling in Automatic1111 WebUI.
CADS greatly increases diversity of generated images by adding scheduled noise to the conditioning at inference time.
- SD XL support
- SD 1.5 support
- Hi-res fix support
- Support restoring parameter values from infotext (Send to Txt2Img, Send to Img2Img, etc.)
- Write infotext to image grids
- X/Y/Z plot support
- ControlNet support
- The authors of the original paper for their method (https://arxiv.org/abs/2310.17347):
@inproceedings{ sadat2024cads, title={{CADS}: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling}, author={Seyedmorteza Sadat and Jakob Buhmann and Derek Bradley and Otmar Hilliges and Romann M. Weber}, booktitle={The Twelfth International Conference on Learning Representations}, year={2024}, url={https://openreview.net/forum?id=zMoNrajk2X} }
- @udon-universe's extension templates (https://github.com/udon-universe/stable-diffusion-webui-extension-templates)