opencv_contrib/modules/dnns_easily_fooled/README.md

Fooling Code

This is the code base used to reproduce the "fooling" images in the paper: Nguyen A, Yosinski J, Clune J. "Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images". In Computer Vision and Pattern Recognition (CVPR '15), IEEE, 2015.

If you use this software in an academic article, please cite:

@inproceedings{nguyen2015deep,
  title={Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images},
  author={Nguyen, Anh and Yosinski, Jason and Clune, Jeff},
  booktitle={Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on},
  year={2015},
  organization={IEEE}
}

For more information regarding the paper, please visit www.evolvingai.org/fooling

Requirements

This is an installation process that requires two main software packages (included in this package):

1. Caffe: http://caffe.berkeleyvision.org

• Our libraries installed to work with Caffe
  • 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
  • Boost 1.52
  • g++ 4.9 (a C++ compiler compatible with C++11 standard)
• 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.