Grad-CAM implementation in Keras

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).

Usage: python grad-cam.py <path_to_image>

Examples

Example image from the original implementation:

'boxer' (243 or 242 in keras)

'tiger cat' (283 or 282 in keras)