From 72372a78089eaaf5ee25bebee4c2016770ad1a56 Mon Sep 17 00:00:00 2001 From: Anh Nguyen Date: Sat, 21 Nov 2015 12:03:51 -0700 Subject: [PATCH] Updated README.md for download scripts --- modules/dnns_easily_fooled/README.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/modules/dnns_easily_fooled/README.md b/modules/dnns_easily_fooled/README.md index e605e57b3..79e9637e2 100644 --- a/modules/dnns_easily_fooled/README.md +++ b/modules/dnns_easily_fooled/README.md @@ -24,6 +24,9 @@ This is an installation process that requires two main software packages (includ * Cuda 6.0 * Boost 1.52 * g++ 4.6 + * Use the provided scripts to download the correct version of Caffe for your experiments. + * `./download_caffe_evolutionary_algorithm.sh` Caffe version for EA experiments + * `./download_caffe_gradient_ascent.sh` Caffe version for gradient ascent experiments 2. Sferes: https://github.com/jbmouret/sferes2 * Our libraries installed to work with Sferes * OpenCV 2.4.10 @@ -41,7 +44,7 @@ Please see the [Installation_Guide](https://github.com/Evolving-AI-Lab/fooling/w * 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 use the `ascent` branch instead of master, because the two required versions of Caffe are different. +* 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. ## Updates