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Research project: Utility-preserving data privatization
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<img src="http://forthebadge.com/images/badges/made-with-python.svg" />Overview | Requirements | Steps
Overview
This repository contains code for reproducing the experiments with a Generative Adversarial Privatizer , based on the Siamese Generative Adversarial Privatizer for Biometric Data. Note that the NIST Special Database 4 (FIGS), of the fingerprints, has been withdrawn from public use, thus it is not used in this repository.
Requirements
• Python 3.5
• PyTorch 0.3 & torchvision
Steps
0. Setup
pip install -r requirements.txt
1. Dataset preparation
Two datasets, FERG and CelebA can be downloaded and extracted by only setting --dataset argument to either "FERG" or "CelebA".
For other datasets new dataloaders have to be written.
2. Siamese GAN training
Run in background/separate session:
tensorboard --logdir runs
Train model on FERG dataset with TensorBoard visualizations:
python src/generative_siamese/generator_plus_siamese_main.py --tensorboard