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https://github.com/Aloereed/stable-diffusion-webui-arc-directml

A proven usable Stable diffusion webui project on Intel Arc GPU with DirectML
https://github.com/Aloereed/stable-diffusion-webui-arc-directml

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A proven usable Stable diffusion webui project on Intel Arc GPU with DirectML

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README 

        
# Stable Diffusion web UI for Intel Arc with DirectML

Forked from [lshqqytiger/stable-diffusion-webui-directml](https://github.com/lshqqytiger/stable-diffusion-webui-directml). The code was fine-tuned only for the errors reported for the Intel Arc GPU.   [中文自述文件在这里.](README_ZH.md)  



**For Stable Diffusion in Linux/WSL using IPEX (Intel Extensions for Pytorch) see here. [Aloereed/stable-diffusion-webui-ipex-arc](https://github.com/Aloereed/stable-diffusion-webui-ipex-arc)  . This approach uses less video memory, generates larger images, and reduces the whine of Intel graphics cards during processing.**



This repository is just to document a version of webui that is verified to be available for the Intel Arc GPU (and very, very minor code tweaks). To get the latest webui features, you can check [here](https://github.com/lshqqytiger/stable-diffusion-webui-directml) directly.



## Requirements

+ An Intel Arc GPU with the latest gfx

+ Windows 11 64 Bit

+ A Python environment

  

If you are using an nVidia GPU, you can [go here](https://github.com/AUTOMATIC1111/stable-diffusion-webui). AMD GPU [here](https://github.com/lshqqytiger/stable-diffusion-webui-directml).  



## Test Enviroment

+ Intel Arc A770 16G

+ Driver: 31.0.101.4125

+ Windows 11 22H2

+ Model: anything-v4.0-pruned-fp32 (running in fp16 however)



A browser interface based on Gradio library for Stable Diffusion.



![Preview](screenshot.png)  



![Usage](usage.png)



## Issues

+ You should generate images up to 512x512. 512x512 is probably a critical point even for A770 16GB. Or you can try "set COMMANDLINE_ARGS= --opt-sub-quad-attention --lowvram --disable-nan-check" in webui-user.bat, but it would be much slower. A380/A750 also should try this line.

+ The same case to Hires.fix

+ If you have multiple DirectML devices on your computer, you may need to check [here](https://github.com/lshqqytiger/stable-diffusion-webui-directml). Or modify [modules/devices.py](modules/devices.py).

## Setup

Just run webui-user.bat. You should also download some repositories first. (Repos include BLIP, CodeFromer, [k-diffusion](https://github.com/lshqqytiger/k-diffusion-directml/tree/891466a373cef42ce7ac3dd840dbba6d832b024b), [stable-diffusion-stability-ai](https://github.com/lshqqytiger/stablediffusion-directml/tree/890e30734bece57c05ed6849c9453359c3511844),taming-transformes)  



## Features

[Detailed feature showcase with images](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features):

- Original txt2img and img2img modes

- One click install and run script (but you still must install python and git)

- Outpainting

- Inpainting

- Color Sketch

- Prompt Matrix

- Stable Diffusion Upscale

- Attention, specify parts of text that the model should pay more attention to

    - a man in a ((tuxedo)) - will pay more attention to tuxedo

    - a man in a (tuxedo:1.21) - alternative syntax

    - select text and press ctrl+up or ctrl+down to automatically adjust attention to selected text (code contributed by anonymous user)

- Loopback, run img2img processing multiple times

- X/Y/Z plot, a way to draw a 3 dimensional plot of images with different parameters

- Textual Inversion

    - have as many embeddings as you want and use any names you like for them

    - use multiple embeddings with different numbers of vectors per token

    - works with half precision floating point numbers

    - train embeddings on 8GB (also reports of 6GB working)

- Extras tab with:

    - GFPGAN, neural network that fixes faces

    - CodeFormer, face restoration tool as an alternative to GFPGAN

    - RealESRGAN, neural network upscaler

    - ESRGAN, neural network upscaler with a lot of third party models

    - SwinIR and Swin2SR([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers

    - LDSR, Latent diffusion super resolution upscaling

- Resizing aspect ratio options

- Sampling method selection

    - Adjust sampler eta values (noise multiplier)

    - More advanced noise setting options

- Interrupt processing at any time

- 4GB video card support (also reports of 2GB working)

- Correct seeds for batches

- Live prompt token length validation

- Generation parameters

     - parameters you used to generate images are saved with that image

     - in PNG chunks for PNG, in EXIF for JPEG

     - can drag the image to PNG info tab to restore generation parameters and automatically copy them into UI

     - can be disabled in settings

     - drag and drop an image/text-parameters to promptbox

- Read Generation Parameters Button, loads parameters in promptbox to UI

- Settings page

- Running arbitrary python code from UI (must run with --allow-code to enable)

- Mouseover hints for most UI elements

- Possible to change defaults/mix/max/step values for UI elements via text config

- Tiling support, a checkbox to create images that can be tiled like textures

- Progress bar and live image generation preview

    - Can use a separate neural network to produce previews with almost none VRAM or compute requirement

- Negative prompt, an extra text field that allows you to list what you don't want to see in generated image

- Styles, a way to save part of prompt and easily apply them via dropdown later

- Variations, a way to generate same image but with tiny differences

- Seed resizing, a way to generate same image but at slightly different resolution

- CLIP interrogator, a button that tries to guess prompt from an image

- Prompt Editing, a way to change prompt mid-generation, say to start making a watermelon and switch to anime girl midway

- Batch Processing, process a group of files using img2img

- Img2img Alternative, reverse Euler method of cross attention control

- Highres Fix, a convenience option to produce high resolution pictures in one click without usual distortions

- Reloading checkpoints on the fly

- Checkpoint Merger, a tab that allows you to merge up to 3 checkpoints into one

- [Custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Scripts) with many extensions from community

- [Composable-Diffusion](https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/), a way to use multiple prompts at once

     - separate prompts using uppercase `AND`

     - also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`

- No token limit for prompts (original stable diffusion lets you use up to 75 tokens)

- DeepDanbooru integration, creates danbooru style tags for anime prompts

- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add --xformers to commandline args)

- via extension: [History tab](https://github.com/yfszzx/stable-diffusion-webui-images-browser): view, direct and delete images conveniently within the UI

- Generate forever option

- Training tab

     - hypernetworks and embeddings options

     - Preprocessing images: cropping, mirroring, autotagging using BLIP or deepdanbooru (for anime)

- Clip skip

- Hypernetworks

- Loras (same as Hypernetworks but more pretty)

- A sparate UI where you can choose, with preview, which embeddings, hypernetworks or Loras to add to your prompt. 

- Can select to load a different VAE from settings screen

- Estimated completion time in progress bar

- API

- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML.

- via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embeds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))

- [Stable Diffusion 2.0](https://github.com/Stability-AI/stablediffusion) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20) for instructions

- [Alt-Diffusion](https://arxiv.org/abs/2211.06679) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#alt-diffusion) for instructions

- Now without any bad letters!

- Load checkpoints in safetensors format

- Eased resolution restriction: generated image's domension must be a multiple of 8 rather than 64

- Now with a license!

- Reorder elements in the UI from settings screen

- 



## Installation and Running

Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD/Intel](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.



Alternatively, use online services (like Google Colab):



- [List of Online Services](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services)



### Automatic Installation on Windows

1. Install [Python 3.10.6](https://www.python.org/downloads/windows/), checking "Add Python to PATH"

2. Install [git](https://git-scm.com/download/win).

3. Download the stable-diffusion-webui repository, for example by running `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git`.

4. Place stable diffusion checkpoint (`model.ckpt`) in the `models/Stable-diffusion` directory (see [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) for where to get it).

5. Run `webui-user.bat` from Windows Explorer as normal, non-administrator, user.



### Automatic Installation on Linux

1. Install the dependencies:

```bash

# Debian-based:

sudo apt install wget git python3 python3-venv

# Red Hat-based:

sudo dnf install wget git python3

# Arch-based:

sudo pacman -S wget git python3

```

2. To install in `/home/$(whoami)/stable-diffusion-webui/`, run:

```bash

bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh)

```



### Installation on Apple Silicon



Find the instructions [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Installation-on-Apple-Silicon).



## Contributing

Here's how to add code to this repo: [Contributing](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Contributing)



## Documentation

The documentation was moved from this README over to the project's [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki).



## Credits

Licenses for borrowed code can be found in `Settings -> Licenses` screen, and also in `html/licenses.html` file.



- Stable Diffusion - https://github.com/CompVis/stable-diffusion, https://github.com/CompVis/taming-transformers

- k-diffusion - https://github.com/crowsonkb/k-diffusion.git

- GFPGAN - https://github.com/TencentARC/GFPGAN.git

- CodeFormer - https://github.com/sczhou/CodeFormer

- ESRGAN - https://github.com/xinntao/ESRGAN

- SwinIR - https://github.com/JingyunLiang/SwinIR

- Swin2SR - https://github.com/mv-lab/swin2sr

- LDSR - https://github.com/Hafiidz/latent-diffusion

- MiDaS - https://github.com/isl-org/MiDaS

- Ideas for optimizations - https://github.com/basujindal/stable-diffusion

- Cross Attention layer optimization - Doggettx - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.

- Cross Attention layer optimization - InvokeAI, lstein - https://github.com/invoke-ai/InvokeAI (originally http://github.com/lstein/stable-diffusion)

- Sub-quadratic Cross Attention layer optimization - Alex Birch (https://github.com/Birch-san/diffusers/pull/1), Amin Rezaei (https://github.com/AminRezaei0x443/memory-efficient-attention)

- Textual Inversion - Rinon Gal - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas).

- Idea for SD upscale - https://github.com/jquesnelle/txt2imghd

- Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot

- CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator

- Idea for Composable Diffusion - https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch

- xformers - https://github.com/facebookresearch/xformers

- DeepDanbooru - interrogator for anime diffusers https://github.com/KichangKim/DeepDanbooru

- Sampling in float32 precision from a float16 UNet - marunine for the idea, Birch-san for the example Diffusers implementation (https://github.com/Birch-san/diffusers-play/tree/92feee6)

- Instruct pix2pix - Tim Brooks (star), Aleksander Holynski (star), Alexei A. Efros (no star) - https://github.com/timothybrooks/instruct-pix2pix

- Security advice - RyotaK

- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.

- (You)