Skip to content

Latest commit

 

History

History
188 lines (169 loc) · 12.5 KB

README_ZH.md

File metadata and controls

188 lines (169 loc) · 12.5 KB
Raw

Stable Diffusion web UI for Intel Arc with DirectML

Forked from lshqqytiger/stable-diffusion-webui-directml. 该代码仅针对英特尔Arc GPU的报告错误进行了微调。
关于在Linux中使用IPEX（Intel Extensions for Pytorch）的SD，见这里。Aloereed/stable-diffusion-webui-ipex-arc 。这种方法使用较少的显存，生成较大的图像，并减少英特尔显卡在处理过程中的啸叫.

这个资源库只是为了记录一个经过验证可以用于Intel Arc GPU的webui版本（以及非常非常小的代码调整）。要获得最新的webui功能，你可以直接查看这里。

要求

  • 英特尔Arc GPU和最新的图形处理驱动。
  • Windows 11 64位
  • 一个Python环境

如果你使用的是nVidia GPU，你可以到这里。AMD GPU 这里。

测试环境

  • Intel Arc A770 16G
  • 驱动程序。31.0.101.4125
  • Windows 11 22H2
  • 模型：anything-v4.0-pruned-fp32（然而在fp16中运行）。

一个基于Gradio库的浏览器界面，用于SD。

预览

用量

问题

  • 你应该生成512x512以内的图像。512x512可能是一个临界点，即使对于A770 16GB来说。或者你可以尝试在webui-user.bat中 "set COMMANDLINE_ARGS= --opt-sub-quad-attention --lowvram --disable-nan-check"，但速度会慢很多。A380/A750也应该试试这一行。
  • 同样的情况到Hires.fix
  • 如果你的电脑上有多个DirectML设备，你可能需要检查这里。或者修改modules/devices.py。

设置

只需运行webui-user.bat。请确保以下仓库被下载。(包括 BLIP, CodeFromer, k-diffusion, stable-diffusion-stability-ai,taming-transformes)

Features

Detailed feature showcase with images:

  • 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), 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 with many extensions from community
  • Composable-Diffusion, 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, major speed increase for select cards: (add --xformers to commandline args)
  • via extension: History tab: 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 by RunwayML.
  • via extension: 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)
  • Stable Diffusion 2.0 support - see wiki for instructions
  • Alt-Diffusion support - see wiki 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 are met and follow the instructions available for both NVidia (recommended) and AMD/Intel GPUs.

Alternatively, use online services (like Google Colab):

Automatic Installation on Windows

  1. Install Python 3.10.6, checking "Add Python to PATH"
  2. Install git.
  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 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:
# 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
  1. To install in /home/$(whoami)/stable-diffusion-webui/, run:
bash <(wget -qO- https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh)

Installation on Apple Silicon

Find the instructions here.

Contributing

Here's how to add code to this repo: Contributing

Documentation

The documentation was moved from this README over to the project's wiki.

Credits

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