leeyegy / feature-distillation

Python implementation for paper: Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples

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demo - how to start-up

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Demo - Start-up

4f9a70bfec15a9e143ff83d1f657a2558121f534 =======

Demo - Start-up

4f9a70bfec15a9e143ff83d1f657a2558121f534 I have changed some source codes so that Feature-dis can be tested on dataset Cifar10.

To run this code, you have to follow these three steps:

• 1. make a new directory named checkpoint/cifar10, and put a pre-trained network model file (wide-resnet-28x10.t7) in this new created directory.
• 2. make a new directory named data, and put data files of Cifar10 here.
• 3. run demo.sh

NOTICE feature-distillation

This repository implements DNN-Oriented JPEG compression introduced in the following paper

Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples