ReDiffusion

The code for the ICML 2023 paper ReDi: Efficient Learning-Free Diffusion Inference via Trajectory Retrieval.

Installation

1. Install diffusers from source.

git clone https://github.com/huggingface/diffusers.git
cd diffusers
git checkout 25f1142
pip install -e .

2. Put the pipeline_re_sd.py in ./src/diffusers/pipelines and import it in ./src/diffusers/__init__.py.

Knowledge Base Creation

1. Follow this (instruction)[https://github.com/facebookresearch/faiss/blob/main/INSTALL.md] to install faiss-cpu.

2. Run traj.py to construct the knowledge base.

Image generation

1. retrieve_val10.py gives an example of generating images with ReDi one by one.

2. retrieve_redi.py gives an example of generating images with ReDi in batches.