Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/IrisRainbowNeko/DreamArtist-stable-diffusion
stable diffusion webui with contrastive prompt tuning
https://github.com/IrisRainbowNeko/DreamArtist-stable-diffusion
Last synced: about 1 month ago
JSON representation
stable diffusion webui with contrastive prompt tuning
- Host: GitHub
- URL: https://github.com/IrisRainbowNeko/DreamArtist-stable-diffusion
- Owner: IrisRainbowNeko
- Created: 2022-10-14T07:25:41.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2022-11-23T02:22:28.000Z (about 2 years ago)
- Last Synced: 2024-05-19T00:27:16.205Z (7 months ago)
- Language: Python
- Homepage:
- Size: 287 MB
- Stars: 871
- Watchers: 13
- Forks: 54
- Open Issues: 17
-
Metadata Files:
- Readme: README.md
- Codeowners: CODEOWNERS
Awesome Lists containing this project
- awesome - IrisRainbowNeko/DreamArtist-stable-diffusion - stable diffusion webui with contrastive prompt tuning (Python)
README
# DreamArtist
Paper: [](https://arxiv.org/abs/2211.11337)
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](https://github.com/AUTOMATIC1111/stable-diffusion-webui).
***Stable-Diffusion-webui Extension Version :*** [DreamArtist-sd-webui-extension](https://github.com/7eu7d7/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.
```bash
git clone https://github.com/7eu7d7/DreamArtist-stable-diffusion
```
Following the [instructions of webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui#automatic-installation-on-windows) 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](https://github.com/7eu7d7/DreamArtist-sd-webui-extension#pre-trained-embeddings)
***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](https://github.com/7eu7d7/DreamArtist-stable-diffusion/releases/tag/embeddings_v2)
| 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
