197 lines
9.2 KiB
Markdown
197 lines
9.2 KiB
Markdown
# Stable Diffusion web UI
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A browser interface based on Gradio library for Stable Diffusion.
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## Feature showcase
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[Detailed feature showcase with images, art by Greg Rutkowski](https://github.com/AUTOMATIC1111/stable-diffusion-webui-feature-showcase)
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- Original txt2img and img2img modes
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- One click install and run script (but you still must install python, git and CUDA)
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- Outpainting
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- Inpainting
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- Prompt matrix
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- Stable Diffusion upscale
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- Attention
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- Loopback
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- X/Y plot
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- Textual Inversion
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- Extras tab with:
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- GFPGAN, neural network that fixes faces
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- RealESRGAN, neural network upscaler
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- ESRGAN, neural network with a lot of third party models
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- Resizing aspect ratio options
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- Sampling method selection
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- Interrupt processing at any time
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- 4GB videocard support
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- Correct seeds for batches
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- Prompt length validation
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- Generation parameters added as text to PNG
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- Tab to view an existing picture's generation parameters
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- Settings page
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- Running custom code from UI
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- Mouseover hints fo most UI elements
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- Possible to change defaults/mix/max/step values for UI elements via text config
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## Installing and running
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You need [python](https://www.python.org/downloads/windows/) and [git](https://git-scm.com/download/win)
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installed to run this, and an NVidia videocard.
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I tested the installation to work Windows with Python 3.8.10, and with Python 3.10.6. You may be able
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to have success with different versions.
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You need `model.ckpt`, Stable Diffusion model checkpoint, a big file containing the neural network weights. You
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can obtain it from the following places:
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- [official download](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original)
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- [file storage](https://drive.yerf.org/wl/?id=EBfTrmcCCUAGaQBXVIj5lJmEhjoP1tgl)
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- magnet:?xt=urn:btih:3a4a612d75ed088ea542acac52f9f45987488d1c&dn=sd-v1-4.ckpt&tr=udp%3a%2f%2ftracker.openbittorrent.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337
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You optionally can use GPFGAN to improve faces, then you'll need to download the model from [here](https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth).
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To use ESRGAN models, put them into ESRGAN directory in the same location as webui.py. A file will be loaded
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as model if it has .pth extension. Grab models from the [Model Database](https://upscale.wiki/wiki/Model_Database).
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### Automatic installation/launch
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- install [Python 3.10.6](https://www.python.org/downloads/windows/) and check "Add Python to PATH" during installation. You must install this exact version.
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- install [git](https://git-scm.com/download/win)
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- install [CUDA 11.3](https://developer.nvidia.com/cuda-11.3.0-download-archive?target_os=Windows&target_arch=x86_64)
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- place `model.ckpt` into webui directory, next to `webui.bat`.
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- _*(optional)*_ place `GFPGANv1.3.pth` into webui directory, next to `webui.bat`.
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- run `webui.bat` from Windows Explorer.
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#### Troublehooting:
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- According to reports, intallation currently does not work in a directory with spaces in filenames.
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- if your version of Python is not in PATH (or if another version is), edit `webui.bat`, change the line `set PYTHON=python` to say the full path to your python executable: `set PYTHON=B:\soft\Python310\python.exe`. You can do this for python, but not for git.
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- if you get out of memory errors and your videocard has low amount of VRAM (4GB), edit `webui.bat`, change line 5 to from `set COMMANDLINE_ARGS=` to `set COMMANDLINE_ARGS=--medvram` (see below for other possible options)
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- installer creates python virtual environment, so none of installed modules will affect your system installation of python if you had one prior to installing this.
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- to prevent the creation of virtual environment and use your system python, edit `webui.bat` replacing `set VENV_DIR=venv` with `set VENV_DIR=`.
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- webui.bat installs requirements from files `requirements_versions.txt`, which lists versions for modules specifically compatible with Python 3.10.6. If you choose to install for a different version of python, editing `webui.bat` to have `set REQS_FILE=requirements.txt` instead of `set REQS_FILE=requirements_versions.txt` may help (but I still reccomend you to just use the recommended version of python).
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- if you feel you broke something and want to reinstall from scratch, delete directories: `venv`, `repositories`.
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## Google collab
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If you don't want or can't run locally, here is google collab that allows you to run the webui:
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https://colab.research.google.com/drive/1Iy-xW9t1-OQWhb0hNxueGij8phCyluOh
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### Manual instructions
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Alternatively, if you don't want to run webui.bat, here are instructions for installing
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everything by hand:
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```commandline
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:: crate a directory somewhere for stable diffusion and open cmd in it;
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:: make sure you are in the right directory; the command must output the directory you chose
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echo %cd%
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:: install torch with CUDA support. See https://pytorch.org/get-started/locally/ for more instructions if this fails.
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pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
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:: check if torch supports GPU; this must output "True". You need CUDA 11. installed for this. You might be able to use
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:: a different version, but this is what I tested.
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python -c "import torch; print(torch.cuda.is_available())"
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:: clone Stable Diffusion repositories
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git clone https://github.com/CompVis/stable-diffusion.git
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git clone https://github.com/CompVis/taming-transformers
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:: install requirements of Stable Diffusion
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pip install transformers==4.19.2 diffusers invisible-watermark
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:: install k-diffusion
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pip install git+https://github.com/crowsonkb/k-diffusion.git
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:: (optional) install GFPGAN to fix faces
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pip install git+https://github.com/TencentARC/GFPGAN.git
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:: go into stable diffusion's repo directory
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cd stable-diffusion
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:: clone web ui
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git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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:: install requirements of web ui
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pip install -r stable-diffusion-webui/requirements.txt
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:: update numpy to latest version
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pip install -U numpy
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:: (outside of command line) put stable diffusion model into models/ldm/stable-diffusion-v1/model.ckpt; you'll have
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:: to create one missing directory;
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:: the command below must output something like: 1 File(s) 4,265,380,512 bytes
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dir models\ldm\stable-diffusion-v1\model.ckpt
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:: (outside of command line) put the GFPGAN model into same directory as webui script
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:: the command below must output something like: 1 File(s) 348,632,874 bytes
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dir stable-diffusion-webui\GFPGANv1.3.pth
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```
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After that the installation is finished.
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Run the command to start web ui:
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```
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python stable-diffusion-webui/webui.py
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```
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If you have a 4GB video card, run the command with either `--lowvram` or `--medvram` argument:
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```
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python stable-diffusion-webui/webui.py --medvram
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```
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After a while, you will get a message like this:
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```
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Running on local URL: http://127.0.0.1:7860/
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```
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Open the URL in browser, and you are good to go.
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### What options to use for low VRAM videocards?
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- If you have 4GB VRAM and want to make 512x512 (or maybe up to 640x640) images, use `--medvram`.
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- If you have 4GB VRAM and want to make 512x512 images, but you get an out of memory error with `--medvram`, use `--medvram --opt-split-attention` instead.
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- If you have 4GB VRAM and want to make 512x512 images, and you still get an out of memory error, use `--lowvram --always-batch-cond-uncond --opt-split-attention` instead.
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- If you have 4GB VRAM and want to make images larger than you can with `--medvram`, use `--lowvram --opt-split-attention`.
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- If you have more VRAM and want to make larger images than you can usually make, use `--medvram --opt-split-attention`. You can use `--lowvram`
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also but the effect will likely be barely noticeable.
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- Otherwise, do not use any of those.
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Extra: if you get a green screen instead of generated pictures, you have a card that doesn't support half
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precision floating point numbers. You must use `--precision full --no-half` in addition to other flags,
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and the model will take much more space in VRAM.
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### How to change UI defaults?
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After running once, a `ui-config.json` file appears in webui directory:
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```json
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{
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"txt2img/Sampling Steps/value": 20,
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"txt2img/Sampling Steps/minimum": 1,
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"txt2img/Sampling Steps/maximum": 150,
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"txt2img/Sampling Steps/step": 1,
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"txt2img/Batch count/value": 1,
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"txt2img/Batch count/minimum": 1,
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"txt2img/Batch count/maximum": 32,
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"txt2img/Batch count/step": 1,
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"txt2img/Batch size/value": 1,
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"txt2img/Batch size/minimum": 1,
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```
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Edit values to your liking and the next time you launch the program they will be applied.
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## Credits
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- Stable Diffusion - https://github.com/CompVis/stable-diffusion, https://github.com/CompVis/taming-transformers
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- k-diffusion - https://github.com/crowsonkb/k-diffusion.git
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- GFPGAN - https://github.com/TencentARC/GFPGAN.git
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- ESRGAN - https://github.com/xinntao/ESRGAN
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- Ideas for optimizations and some code (from users) - https://github.com/basujindal/stable-diffusion
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- Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
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- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
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- (You)
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