rt_bene_standalone

RT-BENE: A Dataset and Baselines for Real-Time Blink Estimation in Natural Environments

License + Attribution

This code is licensed under CC BY-NC-SA 4.0. Commercial usage is not permitted; please contact [email protected] or [email protected] regarding commercial licensing. If you use this dataset or the code in a scientific publication, please cite the following paper:

@inproceedings{CortaceroICCV2019W,
author={Kevin Cortacero and Tobias Fischer and Yiannis Demiris},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision Workshops},
title = {RT-BENE: A Dataset and Baselines for Real-Time Blink Estimation in Natural Environments},
year = {2019},
}

RT-BENE was supported by the EU Horizon 2020 Project PAL (643783-RIA) and a Royal Academy of Engineering Chair in Emerging Technologies to Yiannis Demiris.

More information can be found on the Personal Robotic Lab's website: https://www.imperial.ac.uk/personal-robotics/software/.

Requirements

Please follow the steps given in the Requirements section for the RT-GENE standalone version.

Basic usage

• Run $HOME/rt_gene/rt_gene_standalone/estimate_blink_standalone.py. For supported arguments, run $HOME/rt_gene_standalone/scripts/estimate_blink_standalone.py --help

Optional ensemble model files

• To use an ensemble scheme using multiple models, simply use the --model argument, e.g cd $HOME/rt_gene/ && ./rt_gene_standalone/estimate_blink_standalone.py --models './rt_gene/model_nets/blink_model_1.h5' './rt_gene/model_nets/blink_model_2.h5'

List of libraries

See main README.md