An implementation of the Adversarial Patch paper
adversarial-patch
PyTorch implementation of adversarial patch
This is an implementation of the Adversarial Patch paper. Not official and likely to have bugs/errors.
How to run:
Data set-up:
Run attack:
python make_patch.py --cuda --netClassifier inceptionv3 --max_count 500 --image_size 299 --patch_type circle --outf log
Results:
Using patch shapes of both circles and squares gave good results (both achieved 100% success on the training set and eventually > 90% success on test set)
I managed to recreate the toaster example in the original paper. It looks slightly different but it is evidently a toaster.
This is a toaster
Square patches are a little more homogenous due to that I only rotate by multiples of 90 degrees.
This is also a toaster