This is the official repository accompanying the paper NEUTRON: Neural Particle Swarm Optimization for Material-Aware Inverse Design of Structural Color. link
- clone the repository to your local machine:
git clone https://github.com/hammer-wang/NEUTRON.git
- create a conda envionrment using the provided env configuration file:
conda env create -f environment.yml
Download the train/val/test splits from link. Store the files to ./simulation/multilayer_data/sRGB_400K/
.
- activate the conda environment:
conda activate meta-learning
- run the bash script
bash ./exp_script/run_best.sh
The model checkpoint will be automatically save to the folder./log/
for downstream evaluations.
You can also download a trained model direclty from Google Drive
Please refer to the provided paper_figures.ipynb
notebook.
Please refer to the bash script ./exp_scripts/reconstruct_imgs.sh
.
If you find this repository useful for your research, please consider citing us as:
@article{wang2022neutron,
title={NEUTRON: Neural particle swarm optimization for material-aware inverse design of structural color},
author={Wang, Haozhu and Guo, L Jay},
journal={iScience},
volume={25},
number={5},
pages={104339},
year={2022},
publisher={Elsevier}
}