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README.md

GLIGEN: Open-Set Grounded Text-to-Image Generation (CVPR 2023)

Yuheng Li, Haotian Liu, Qingyang Wu, Fangzhou Mu, Jianwei Yang, Jianfeng Gao, Chunyuan Li*, Yong Jae Lee* (*Co-senior authors)

[Project Page] [Paper] [Demo] [YouTube Video]

🔥 News

  • [2023.03.22] Our fork on diffusers with support of text-box-conditioned generation and inpainting is released. We are working on integrating it into official diffusers code base. More conditions and a new demo is on the way. Stay tuned!

Installation

conda create -n gligen_diffusers python=3.10
conda activate gligen_diffusers
pip install torch torchvision transformers accelerate

git clone git@github.com:gligen/diffusers.git
pip install -e .

Usage

cd examples/gligen

# for text-box conditioned generation.
python generation_text_box.py

# for text-box conditioned inpainting.
python inpainting_text_box.py