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This is not in use anymore. It was made because A1111 refused to make an API in his popular SD implementation. In the meantime he changed his mind and so I switched over official A1111.

Stable Diffusion API

A headless server with REST API for Stable Diffusion and for Krita or Photoshop Plugins.

Installing and running

You need python and git installed to run this, and an NVidia videocard.

I tested the installation to work Windows with Python 3.8.10, and with Python 3.10.6. You may be able to have success with different versions.

You need model.ckpt, Stable Diffusion model checkpoint, a big file containing the neural network weights. You can obtain it from the following places:

  • official download
  • file storage
  • 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

You optionally can use GPFGAN to improve faces, then you'll need to download the model from here.

Automatic installation/launch

  • install Python 3.10.6 Best would be to activate global path checkbox in first dialog.
  • install git
  • install CUDA 11.3
  • place model.ckpt into webui directory, next to api.bat.
  • (optional) place GFPGANv1.3.pth into webui directory, next to api.bat.
  • run webui.bat from Windows Explorer.

Troublehooting:

  • According to reports, intallation currently does not work in a directory with spaces in filenames.
  • if your version of Python is not in PATH (or if another version is), edit api.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.
  • 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)
  • 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.
  • to prevent the creation of virtual environment and use your system python, edit api.bat replacing set VENV_DIR=venv with set VENV_DIR=.
  • api.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 api.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).
  • if you feel you broke something and want to reinstall from scratch, delete directories: venv, repositories.

Manual instructions

Alternatively, if you don't want to run api.bat, here are instructions for installing everything by hand:

:: crate a directory somewhere for stable diffusion and open cmd in it;
:: make sure you are in the right directory; the command must output the directory you chose
echo %cd%

:: install torch with CUDA support. See https://pytorch.org/get-started/locally/ for more instructions if this fails.
pip install torch --extra-index-url https://download.pytorch.org/whl/cu113

:: check if torch supports GPU; this must output "True". You need CUDA 11. installed for this. You might be able to use
:: a different version, but this is what I tested.
python -c "import torch; print(torch.cuda.is_available())"

:: clone Stable Diffusion repositories
git clone https://github.com/CompVis/stable-diffusion.git
git clone https://github.com/CompVis/taming-transformers

:: install requirements of Stable Diffusion
pip install transformers==4.19.2 diffusers invisible-watermark

:: install k-diffusion
pip install git+https://github.com/crowsonkb/k-diffusion.git

:: (optional) install GFPGAN to fix faces
pip install git+https://github.com/TencentARC/GFPGAN.git

:: go into stable diffusion's repo directory
cd stable-diffusion

:: clone web ui (API version)
git clone https://github.com/imperator-maximus/stable-diffusion-webui

:: install requirements of web ui
pip install -r stable-diffusion-webui/requirements.txt

:: update numpy to latest version
pip install -U numpy

:: (outside of command line) put stable diffusion model into models/ldm/stable-diffusion-v1/model.ckpt; you'll have
:: to create one missing directory;
:: the command below must output something like: 1 File(s) 4,265,380,512 bytes
dir models\ldm\stable-diffusion-v1\model.ckpt

:: (outside of command line) put the GFPGAN model into same directory as webui script
:: the command below must output something like: 1 File(s) 348,632,874 bytes
dir stable-diffusion-webui\GFPGANv1.3.pth

After that the installation is finished.

Run the command to start api:

python stable-diffusion-webui/api.py

If you have a 4GB video card, run the command with either --lowvram or --medvram argument:

python stable-diffusion-webui/api.py --medvram

After a while, you will get a message like this:

Running on local URL:  http://127.0.0.1:7860/

Put URL in Krita or Photoshop Plugin Config - that is all. WebUI also runs on same URL in browser.


If there is an issue - test URl in browser. You can  also see  API version at http://127.0.0.1:5000/api/version


### What options to use for low VRAM videocardsd?
- If you have 4GB VRAM and want to make 512x512 (or maybe up to 640x640) images, use `--medvram`.
- If you have 4GB VRAM and want to make 512x512 images, but you get an out of memory error with `--medvram`, use `--lowvram --always-batch-cond-uncond` instead.
- If you have 4GB VRAM and want to make images larger than you can with `--medvram`, use `--lowvram`.
- If you have more VRAM and want to make larger images than you can usually make, use `--medvram`. You can use `--lowvram`
also but the effect will likely be barely noticeable.
- Otherwise, do not use any of those.

Extra: if you get a green screen instead of generated pictures, you have a card that doesn't support half
precision floating point numbers. You must use `--precision full --no-half` in addition to other flags,
and the model will take much more space in VRAM.