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| author | Xavier <xiaozhisheng950@gmail.com> | 2022-09-09 11:41:56 -0700 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2022-09-09 11:41:56 -0700 |
| commit | bb8f4f2dc1d8d1b9ce4f705d03621e6ac8e50028 (patch) | |
| tree | 18007a1e40d3407899b7c6ac3aeed28dc4eb2433 | |
| parent | Update v1-finetune_unfrozen.yaml (diff) | |
Update README.md
| -rw-r--r-- | README.md | 5 |
1 files changed, 5 insertions, 0 deletions
@@ -19,6 +19,11 @@ python scripts/stable_txt2img.py --ddim_eta 0.0 --n_samples 8 --n_iter 1 --scale I generate 8 images for regularization, but more regularization images may lead to stronger regularization and better editability. After that, save the generated images (separately, one image per ```.png``` file) at ```/root/to/regularization/images```. +**Updates on 9/9** +We should definitely use more images for regularization. Please try 100 or 200, to better align with the original paper. To acomodate this, I shorten the "repeat" of reg dataset in the [config file](https://github.com/XavierXiao/Dreambooth-Stable-Diffusion/blob/main/configs/stable-diffusion/v1-finetune_unfrozen.yaml#L96). + +For some cases, if the generated regularization images are highly unrealistic (happens when you want to generate "man" or "woman"), you can find a diverse set of images (of man/woman) online, and use them as regularization images. + ### Training Training can be done by running the following command |