From 258fda0d36d625da77b00cb6a4cf140633517dac Mon Sep 17 00:00:00 2001 From: Ikko Ashimine Date: Fri, 7 Oct 2022 10:05:53 +0900 Subject: [PATCH] Update README.md acomodate -> accommodate enviroment -> environment --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 0b6a8424..29e32fde 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ The implementation makes minimum changes over the official codebase of Textual I ## Usage ### Preparation -First set-up the ```ldm``` enviroment following the instruction from textual inversion repo, or the original Stable Diffusion repo. +First set-up the ```ldm``` environment following the instruction from textual inversion repo, or the original Stable Diffusion repo. To fine-tune a stable diffusion model, you need to obtain the pre-trained stable diffusion models following their [instructions](https://github.com/CompVis/stable-diffusion#stable-diffusion-v1). Weights can be downloaded on [HuggingFace](https://huggingface.co/CompVis). You can decide which version of checkpoint to use, but I use ```sd-v1-4-full-ema.ckpt```. @@ -23,7 +23,7 @@ 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). +We should definitely use more images for regularization. Please try 100 or 200, to better align with the original paper. To accommodate 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.