A project based on further investigating the Grad-CAM explanation method.
This project compares Squad-CAM with other explanation methods like Grad-CAM and guided backprop. The target is DCNN models like Resnet, VGG16 or AlexNet. This project uses VGG16 as a base for experiments. This requires all images to be of size 224x224. We opted not to resize images due to distortions.
Project is created with:
- Tensorflow version: 2.1.0
- Keras version: 2.3.1
To run this project, set up a conda enviroment and run
$ pip install -r requirements.txt
Analyze a set of photos by defining the source and target folders
$ python Squad-CAM -source images/*.png -target output