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Greatly increase the diversity of your generated images in Automatic1111 WebUI through Condition-Annealed Sampling.

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sd-webui-cads

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.

image

PR's are welcome!

Feature / To-do List

  • 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

Credits

  • 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)

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Greatly increase the diversity of your generated images in Automatic1111 WebUI through Condition-Annealed Sampling.

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