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Update README.md (#1455)
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Changed the links for GFPGAN, it was still pointing to the v1.3 version
instead of v1.4, this is why we get so many issues with people not
having the proper model downloaded.
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@ZeroCool940711
ZeroCool940711 committed Oct 6, 2022
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## [Visit sd-webui's Discord Server](https://discord.gg/gyXNe4NySY) [![Discord Server](https://user-images.githubusercontent.com/5977640/190528254-9b5b4423-47ee-4f24-b4f9-fd13fba37518.png)](https://discord.gg/gyXNe4NySY)

## Installation instructions for:

- **[Windows](https://sd-webui.github.io/stable-diffusion-webui/docs/1.windows-installation.html)**
- **[Linux](https://sd-webui.github.io/stable-diffusion-webui/docs/2.linux-installation.html)**

Expand All @@ -20,21 +21,30 @@ Come to our [Discord Server](https://discord.gg/gyXNe4NySY) or use [Discussions]

Check the [Contribution Guide](CONTRIBUTING.md)

[sd-webui](https://github.com/sd-webui) is:
[sd-webui](https://github.com/sd-webui) main devs:

* ![hlky's avatar](https://avatars.githubusercontent.com/u/106811348?s=40&v=4) [hlky](https://github.com/hlky)
* ![ZeroCool940711's avatar](https://avatars.githubusercontent.com/u/5977640?s=40&v=4)[ZeroCool940711](https://github.com/ZeroCool940711)
* ![codedealer's avatar](https://avatars.githubusercontent.com/u/4258136?s=40&v=4)[codedealer](https://github.com/codedealer)

### Project Features:

* Two great Web UI's to choose from: Streamlit or Gradio

* No more manually typing parameters, now all you have to do is write your prompt and adjust sliders

* Built-in image enhancers and upscalers, including GFPGAN and realESRGAN

* Run additional upscaling models on CPU to save VRAM

* Textual inversion 🔥: [info](https://textual-inversion.github.io/) - requires enabling, see [here](https://github.com/hlky/sd-enable-textual-inversion), script works as usual without it enabled

* Advanced img2img editor with Mask and crop capabilities

* Mask painting 🖌️: Powerful tool for re-generating only specific parts of an image you want to change (currently Gradio only)

* More diffusion samplers 🔥🔥: A great collection of samplers to use, including:

- `k_euler` (Default)
- `k_lms`
- `k_euler_a`
Expand All @@ -45,28 +55,41 @@ Check the [Contribution Guide](CONTRIBUTING.md)
- `DDIM`

* Loopback ➿: Automatically feed the last generated sample back into img2img

* Prompt Weighting 🏋️: Adjust the strength of different terms in your prompt

* Selectable GPU usage with `--gpu <id>`

* Memory Monitoring 🔥: Shows VRAM usage and generation time after outputting

* Word Seeds 🔥: Use words instead of seed numbers

* CFG: Classifier free guidance scale, a feature for fine-tuning your output

* Automatic Launcher: Activate conda and run Stable Diffusion with a single command

* Lighter on VRAM: 512x512 Text2Image & Image2Image tested working on 4GB

* Prompt validation: If your prompt is too long, you will get a warning in the text output field

* Copy-paste generation parameters: A text output provides generation parameters in an easy to copy-paste form for easy sharing.

* Correct seeds for batches: If you use a seed of 1000 to generate two batches of two images each, four generated images will have seeds: `1000, 1001, 1002, 1003`.

* Prompt matrix: Separate multiple prompts using the `|` character, and the system will produce an image for every combination of them.
* Loopback for Image2Image: A checkbox for img2img allowing to automatically feed output image as input for the next batch. Equivalent to saving output image, and replacing input image with it.

* Loopback for Image2Image: A checkbox for img2img allowing to automatically feed output image as input for the next batch. Equivalent to saving output image, and replacing input image with it.

# Stable Diffusion Web UI

A fully-integrated and easy way to work with Stable Diffusion right from a browser window.

## Streamlit

![](images/streamlit/streamlit-t2i.png)

**Features:**

- Clean UI with an easy to use design, with support for widescreen displays.
- Dynamic live preview of your generations
- Easily customizable presets right from the WebUI (Coming Soon!)
Expand All @@ -80,12 +103,12 @@ A fully-integrated and easy way to work with Stable Diffusion right from a brows

Please see the [Streamlit Documentation](docs/4.streamlit-interface.md) to learn more.


## Gradio

![](images/gradio/gradio-t2i.png)

**Features:**

- Older UI design that is fully functional and feature complete.
- Has access to all upscaling models, including LSDR.
- Dynamic prompt entry automatically changes your generation settings based on `--params` in a prompt.
Expand All @@ -94,7 +117,6 @@ Please see the [Streamlit Documentation](docs/4.streamlit-interface.md) to learn

Please see the [Gradio Documentation](docs/5.gradio-interface.md) to learn more.


## Image Upscalers

---
Expand All @@ -106,7 +128,7 @@ Please see the [Gradio Documentation](docs/5.gradio-interface.md) to learn more.
Lets you improve faces in pictures using the GFPGAN model. There is a checkbox in every tab to use GFPGAN at 100%, and also a separate tab that just allows you to use GFPGAN on any picture, with a slider that controls how strong the effect is.

If you want to use GFPGAN to improve generated faces, you need to install it separately.
Download [GFPGANv1.3.pth](https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth) and put it
Download [GFPGANv1.4.pth](https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth) and put it
into the `/stable-diffusion-webui/models/gfpgan` directory.

### RealESRGAN
Expand All @@ -119,18 +141,26 @@ There is also a separate tab for using RealESRGAN on any picture.
Download [RealESRGAN_x4plus.pth](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth) and [RealESRGAN_x4plus_anime_6B.pth](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth).
Put them into the `stable-diffusion-webui/models/realesrgan` directory.

### GoBig, LSDR, and GoLatent *(Currently Gradio Only)*


### LSDR

Download **LDSR** [project.yaml](https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1) and [model last.cpkt](https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1). Rename last.ckpt to model.ckpt and place both under `stable-diffusion-webui/models/ldsr/`

### GoBig, and GoLatent *(Currently on the Gradio version Only)*

More powerful upscalers that uses a seperate Latent Diffusion model to more cleanly upscale images.

Download **LDSR** [project.yaml](https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1) and [ model last.cpkt](https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1). Rename last.ckpt to model.ckpt and place both under stable-diffusion-webui/models/ldsr/


Please see the [Image Enhancers Documentation](docs/5.image_enhancers.md) to learn more.

-----

### *Original Information From The Stable Diffusion Repo*

# Stable Diffusion

*Stable Diffusion was made possible thanks to a collaboration with [Stability AI](https://stability.ai/) and [Runway](https://runwayml.com/) and builds upon our previous work:*

[**High-Resolution Image Synthesis with Latent Diffusion Models**](https://ommer-lab.com/research/latent-diffusion-models/)<br/>
Expand All @@ -144,7 +174,6 @@ Please see the [Image Enhancers Documentation](docs/5.image_enhancers.md) to lea

which is available on [GitHub](https://github.com/CompVis/latent-diffusion). PDF at [arXiv](https://arxiv.org/abs/2112.10752). Please also visit our [Project page](https://ommer-lab.com/research/latent-diffusion-models/).


[Stable Diffusion](#stable-diffusion-v1) is a latent text-to-image diffusion
model.
Thanks to a generous compute donation from [Stability AI](https://stability.ai/) and support from [LAION](https://laion.ai/), we were able to train a Latent Diffusion Model on 512x512 images from a subset of the [LAION-5B](https://laion.ai/blog/laion-5b/) database.
Expand All @@ -164,15 +193,14 @@ then finetuned on 512x512 images.
in its training data.
Details on the training procedure and data, as well as the intended use of the model can be found in the corresponding [model card](https://huggingface.co/CompVis/stable-diffusion).

## Comments
## Comments

- Our codebase for the diffusion models builds heavily on [OpenAI's ADM codebase](https://github.com/openai/guided-diffusion)
and [https://github.com/lucidrains/denoising-diffusion-pytorch](https://github.com/lucidrains/denoising-diffusion-pytorch).
Thanks for open-sourcing!
and [https://github.com/lucidrains/denoising-diffusion-pytorch](https://github.com/lucidrains/denoising-diffusion-pytorch).
Thanks for open-sourcing!

- The implementation of the transformer encoder is from [x-transformers](https://github.com/lucidrains/x-transformers) by [lucidrains](https://github.com/lucidrains?tab=repositories).


## BibTeX

```
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}
```


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