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stablediffusion-infinity
Outpainting with Stable Diffusion on an infinite canvas.
Start with init_image:
https://user-images.githubusercontent.com/1665437/190231611-fc263115-0fb9-4f2d-a71b-7e500c1e311d.mp4
Start with text2img:
https://user-images.githubusercontent.com/1665437/190212025-f4a82c46-0ff1-4ca2-b79b-6c81601e3eed.mp4
It is recommended to run the notebook on a local server for better interactive control.
The notebook might work on Windows (see this issue https://github.com/lkwq007/stablediffusion-infinity/issues/12 for more information) and Apple Silicon devices (untested, check guide here: https://huggingface.co/docs/diffusers/optimization/mps).
Status
This project mainly works as a proof of concept. In that case, the UI design is relatively weak, and the quality of results is not guaranteed. You may need to do prompt engineering or change the size of the selection box to get better outpainting results.
Pull requests are welcome for better UI control, ideas to achieve better results, or any other improvements.
Setup environment
setup with environment.yml
git clone --recurse-submodules https://github.com/lkwq007/stablediffusion-infinity
cd stablediffusion-infinity
conda env create -f environment.yml
if the environment.yml
doesn't work for you, you may install dependencies manually:
conda create -n sd-inf python=3.10
conda activate sd-inf
conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
conda install scipy scikit-image
conda install -c conda-forge diffusers transformers ftfy
pip install opencv-python
pip install gradio==3.4
For windows, you may need to replace pip install opencv-python
with conda install -c conda-forge opencv
CPP library (optional)
Note that opencv
library (e.g. libopencv-dev
/opencv-devel
, the package name may differ on different distributions) is required for PyPatchMatch
. You may need to install opencv
by yourself. If no opencv
installed, the patch_match
option (usually better quality) won't work.
How-to
conda activate sd-inf
python app.py
Running with Docker
This should get you started without needing to manually install anything, except for having an environment with Docker installed and an Nvidia GPU. This has been tested on Docker Desktop on Windows 10 using the WSL2 backend.
First, update the .env file with your Huggingface token from https://huggingface.co/settings/tokens
Open your shell that has docker and run these commands
cd stablediffusion-infinity
docker-compose build
docker-compose up
Watch the log for the url to open in your browser. Choose the one that starts with http://127.0.0.1:8888/
FAQs
- Troubleshooting on Windows:
- False positive rate of safety checker is quite high:
- What is the init_mode
- init_mode indicates how to fill the empty/masked region, usually
patch_match
is better than others
- init_mode indicates how to fill the empty/masked region, usually
- The GUI is lagging on colab
- It is recommended to run the notebook on a local server since the interactions and canvas content updates are actually handled by the python backend on the serverside, and that's how
ipycanvas
works - colab doesn't support the latest version of
ipycanvas
, which may have better performance
- It is recommended to run the notebook on a local server since the interactions and canvas content updates are actually handled by the python backend on the serverside, and that's how
Credit
The code of perlin2d.py
is from https://stackoverflow.com/questions/42147776/producing-2d-perlin-noise-with-numpy/42154921#42154921 and is not included in the scope of LICENSE used in this repo.