From abc7bc838d6b1966d10f08d555f6ec64c941ab80 Mon Sep 17 00:00:00 2001 From: Anh Nguyen Date: Sun, 29 Nov 2015 21:27:14 -0700 Subject: [PATCH] Update README.md --- modules/dnns_easily_fooled/README.md | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/modules/dnns_easily_fooled/README.md b/modules/dnns_easily_fooled/README.md index c3b9a8618..532c0a76c 100644 --- a/modules/dnns_easily_fooled/README.md +++ b/modules/dnns_easily_fooled/README.md @@ -33,3 +33,12 @@ This is an installation process that requires two main software packages (includ * Use the provided script `./download_sferes.sh` to download the correct version of Sferes. Note: These are patched versions of the two frameworks with our additional work necessary to produce the images as in the paper. They are not the same as their master branches. + +## Installation +Please see the [Installation_Guide](https://github.com/Evolving-AI-Lab/fooling/wiki/Installation-Guide) for more details. + +## Usage +* An MNIST experiment (Fig. 4, 5 in the paper) can be run directly on a local machine (4-core) within a reasonable amount of time (around ~5 minutes or less for 200 generations). +* An ImageNet experiment needs to be run on a cluster environment. It took us ~4 days x 128 cores to run 5000 generations and produce 1000 images (Fig. 8 in the paper). +* [How to configure an experiment to test the evolutionary framework quickly](https://github.com/Evolving-AI-Lab/fooling/wiki/How-to-test-the-evolutionary-framework-quickly) +* To reproduce the gradient ascent fooling images (Figures 13, S3, S4, S5, S6, and S7 from the paper), see the [documentation in the caffe/ascent directory](https://github.com/anguyen8/opencv_contrib/tree/master/modules/dnns_easily_fooled/caffe/ascent). You'll need to download the correct Caffe version for this experiment using `./download_caffe_gradient_ascent.sh` script.