DALL-E Playground

A playground for DALL-E enthusiasts to tinker with the open-source version of OpenAI's DALL-E, based on DALL-E Mini.

DALLE.Playground.demo.mp4

Fast usage

You can tinker with the DALL-E playground using a Github-hosted frontend. Follow these steps:

1. Run the DALL-E backend using Google Colab
2. Copy the URL from the last executed cell. Look for the line having your url is: https://XXXX.loca.lt
3. Wait for the backend to fully load, this should take ~2min and you should see --> DALL-E Server is up and running!
4. Browse https://saharmor.github.io/dalle-playground/?backendUrl=https://XXXX.loca.lt where the backendUrl query parameter should be the url from the previous step

General note: while it's possible to run the DALL-E Mini backend on the free tier of Google Colab, generating more than 1-2 images would take more than 1min, which will result in a frontend timeout. Consider upgrading to Colab Pro or run the backend notebook on your stronger ML machine (e.g. AWS EC2).

Using DALL-E Mega

DALL-E Mega is substianlly more capable than DALL-E Mini and therefore generates higher fidelity images. If you have the computing power--either through a Google Colab Pro+ subcription or by having a strong local machine, uncomment this line before running the backend.

Local development

Follow these steps in case you'd like to clone and run the DALL-E playground locally:

1. Clone or fork this repository
2. Create a virtual environment cd backend && python3 -m venv ENV_NAME
3. Install requirements pip install -r requirements.txt
4. Make sure you have pytorch and its dependencies installed Installation guide
5. Run web server python app.py
6. In a different terminal, install frontend's modules cd interface && npm install and run it npm start
7. Copy backend's url from step 5 and paste it in the backend's url input within the web app

Acknowledgements

This repo is a full-stack flavour of Boris Dayma's DALL-E Mini repository.