Gradient class activation maps are a visualization technique for deep learning networks.
See the paper: https://arxiv.org/pdf/1610.02391v1.pdf
The paper authors torch implementation: https://github.com/ramprs/grad-cam
This code assumes Tensorflow dimension ordering, and uses the VGG16 network in keras.applications by default (the network weights will be downloaded on first use).
TODO: Combine with guided back propagation like in the paper.
Usage: python grad-cam.py <path_to_image>
