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https://github.com/carefree0910/carefree-creator
AI magics meet Infinite draw board.
https://github.com/carefree0910/carefree-creator
image-to-image inpainting latent-diffusion outpainting pypi python pytorch sketch-to-image stable-diffusion super-resolution text-to-image
Last synced: 4 days ago
JSON representation
AI magics meet Infinite draw board.
- Host: GitHub
- URL: https://github.com/carefree0910/carefree-creator
- Owner: carefree0910
- License: mit
- Created: 2022-09-13T07:40:08.000Z (over 2 years ago)
- Default Branch: dev
- Last Pushed: 2024-05-09T01:47:27.000Z (8 months ago)
- Last Synced: 2024-12-12T22:02:39.651Z (11 days ago)
- Topics: image-to-image, inpainting, latent-diffusion, outpainting, pypi, python, pytorch, sketch-to-image, stable-diffusion, super-resolution, text-to-image
- Language: Jupyter Notebook
- Homepage: https://creator.nolibox.com/guest
- Size: 8.06 MB
- Stars: 2,136
- Watchers: 98
- Forks: 215
- Open Issues: 23
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-stable-diffusion - carefree-creator
- awesome-stable-diffusion - Carefree Creator (local version) - User friendly GUI with a creator/artist centric workflow. (Training / GUIS)
README
An open sourced, AI-powered creator for everyone.
> * This is the backend project of the `Creator` product. If you are looking for the **WebUI** codes, you may checkout the [`carefree-drawboard`](https://github.com/carefree0910/carefree-drawboard) 🎨 project.
>
> * Most of the contents have been moved to the [Wiki](https://github.com/carefree0910/carefree-creator/wiki) page.
### [Wiki](https://github.com/carefree0910/carefree-creator/wiki) | [WebUI Codes](https://github.com/carefree0910/carefree-drawboard)
# Installation
`carefree-creator` is built on top of `carefree-learn`, and requires:
- `Python>=3.8`
- `pytorch>=1.12.0`. Please refer to [PyTorch](https://pytorch.org/get-started/locally/)'s official website, and it is highly recommended to pre-install PyTorch with conda.
## Hardware Requirements
> Related issue: [#10](https://github.com/carefree0910/carefree-creator/issues/10).
This project will eat up 11~13 GB of GPU RAM if no modifications are made, because it actually integrates FIVE different SD versions together, and many other models as well. 🤣
There are two ways that can reduce the usage of GPU RAM - lazy loading and partial loading, see the following [`Run`](#run) section for more details.
## pip installation
```bash
pip install carefree-creator
```
If you are interested in the latest features, you may use `pip` to install from source as well:
```bash
git clone https://github.com/carefree0910/carefree-creator.git
cd carefree-creator
pip install -e .
```
### Run
`carefree-creator` builds a CLI for you to setup your local service. For instance, we can:
```bash
cfcreator serve
```
If you don't have an NVIDIA GPU (e.g. mac), you may try:
```bash
cfcreator serve --cpu
```
If you are using your GPU-powered laptop, you may try:
```bash
cfcreator serve --limit 1
```
> The `--limit` flag is used to limit the number of loading models. By specifying `1`, only the executing model will be loaded, and other models will stay on your disk.
>
> See [#10](https://github.com/carefree0910/carefree-creator/issues/10#issuecomment-1520661893) for more details.
If you have plenty of RAM resources but your GPU RAM is not large enough, you may try:
```bash
cfcreator serve --lazy
```
> With the `--lazy` flag, the models will be loaded to RAM, and only the executing model will be moved to GPU RAM.
>
> So as an exchange, your RAM will be eaten up! 🤣
If you only want to try the SD basic endpoints, you may use:
```bash
cfcreator serve --focus sd.base
```
And if you only want to try the SD anime endpoints, you may use:
```bash
cfcreator serve --focus sd.anime
```
More usages could be found by:
```bash
cfcreator serve --help
```
## Docker
### Prepare
```bash
export TAG_NAME=cfcreator
git clone https://github.com/carefree0910/carefree-creator.git
cd carefree-creator
```
### Build
```bash
docker build -t $TAG_NAME .
```
If your internet environment lands in China, it might be faster to build with `Dockerfile.cn`:
```bash
docker build -t $TAG_NAME -f Dockerfile.cn .
```
### Run
```bash
docker run --gpus all --rm -p 8123:8123 $TAG_NAME:latest
```
# Credits
- [Stable Diffusion](https://github.com/CompVis/stable-diffusion), the foundation of various generation methods.
- [Stable Diffusion from runwayml](https://github.com/runwayml/stable-diffusion), the adopted SD-inpainting method.
- [Waifu Diffusion](https://github.com/harubaru/waifu-diffusion), the anime-finetuned version of Stable Diffusion.
- [Real ESRGAN](https://github.com/xinntao/Real-ESRGAN), the adopted Super Resolution methods.
- [Latent Diffusion](https://github.com/CompVis/latent-diffusion), the adopted Inpainting & Landscape Synthesis method.
- [carefree-learn](https://github.com/carefree0910/carefree-learn), the code base that has re-implemented all the models above and provided clean and handy APIs.
- And You! Thank you for watching!