DreamArtist

Paper:

This repo is the official PyTorch implementation of "DreamArtist: Towards Controllable One-Shot Text-to-Image Generation via Contrastive Prompt-Tuning" with Stable-Diffusion-webui.

Stable-Diffusion-webui Extension Version : DreamArtist-sd-webui-extension

Everyone is an artist. Rome wasn't built in a day, but your artist dreams can be!

With just one training image DreamArtist learns the content and style in it, generating diverse high-quality images with high controllability. Embeddings of DreamArtist can be easily combined with additional descriptions, as well as two learned embeddings.

Setup and Running

Clone this repo.

git clone https://github.com/7eu7d7/DreamArtist-stable-diffusion

Following the instructions of webui to install.

Training and Usage

First create the positive and negative embeddings in DreamArtist Create Embedding Tab.

Preview Setting

After that, the names of the positive and negative embedding ({name} and {name}-neg) should be filled into the txt2img Tab with some common descriptions. This will ensure a correct preview image.

Train

Then, select positive embedding and set the parameters and image folder path in the Train Tab to start training. The corresponding negative embedding is loaded automatically. If your VRAM is low or you want save time, you can uncheck the reconstruction.

Recommended parameters

better to train without filewords

Remember to check the option below, otherwise the preview is wrong.

Inference

Fill the trained positive and negative embedding into txt2img to generate with DreamArtist prompt.

Tested models (need ema version):

• Stable Diffusion v1.5
• animefull-latest
• Anything v3.0

Embeddings can be transferred between different models of the same dataset.

Pre-trained embeddings:

Download

Name	Model	Image	embedding length (Positive, Negative)	iter	lr	cfg scale
ani-nahida	animefull-latest		3, 6	8000	0.0025	3
ani-cocomi	animefull-latest		3, 6	8000	0.0025	3
ani-gura	animefull-latest		3, 6	12000	0.0025	3
ani-g	animefull-latest		3, 10	1500	0.003	5
asty-bk	animefull-latest		3, 6	5000	0.003	3
asty-gc	animefull-latest		3, 10	1000	0.005	5
real-dog	sd v1.4		3, 3	1000	0.005	5
real-sship	sd v1.4		3, 3	3000	0.003	5
sty-cyber	sd v1.4		3, 5	15000	0.0025	5
sty-shuimo	sd v1.4		3, 5	15000	0.0025	5

Style Clone

Prompt Compositions

Comparison on One-Shot Learning

Other Results