Code accompanying the paper.
Open Access Paper on Wiley WIREs Journal of Data Mining and Knowledge Discovery
Gaudio, A., Smailagic, A., Faloutsos, C., Mohan, S., Johnson, E., Liu, Y., Costa, P., & Campilho, A. (2023). DeepFixCX: Explainable privacy-preserving image compression for medical image analysis. WIREs Data Mining and Knowledge Discovery, e1495. https://doi.org/10.1002/widm.1495
@article{deepfixcx,
author = {Gaudio, Alex and Smailagic, Asim and Faloutsos, Christos and Mohan, Shreshta and Johnson, Elvin and Liu, Yuhao and Costa, Pedro and Campilho, Aurélio},
title = {DeepFixCX: Explainable privacy-preserving image compression for medical image analysis},
journal = {WIREs Data Mining and Knowledge Discovery},
volume = {n/a},
number = {n/a},
pages = {e1495},
keywords = {compression, deep networks, explainability, medical image analysis, privacy, wavelets},
doi = {https://doi.org/10.1002/widm.1495},
url = {https://wires.onlinelibrary.wiley.com/doi/abs/10.1002/widm.1495},
eprint = {https://wires.onlinelibrary.wiley.com/doi/pdf/10.1002/widm.1495},
}
All experiments are in ./bin/experiments.sh
and ./bin/experiments_extended.sh
It's research quality code. Please open a GitHub issue if there is a reproducibility problem. Note that the name was "DeepFix" and then we changed it to "DeepFixCX".
# cd into the root of the repository.
# Install libraries
pip install -r requirements.txt
pip install . # install deepfix if you want.
Comments are in the docstrings.
# DeepFixCX: Compress and privatize images:
from deepfixcx.models import DeepFixCXImg2Img
# Wavelet Packet layer may be useful in projects:
from deepfixcx.models.wavelet_packet import WaveletPacket2d
# DeepFixCX: just the compression or reconstruction parts.
from deepfixcx.models import DeepFixCXCompression, DeepFixCXReconstruct