A tensorflow implementation of "Information-Theoretic Visual Explanation for Black-Box Classifiers"
An parachute image was classified as a balloon.
- The IG map provides a class-independent explanation: the classifier made a decision based on the highlighted object (the parachute and the rope).
- The PMI map provides a class-specific explanation for the balloon class: the orange fabric looks a balloon, but the rope doesn't.
The code runs on python 3.7 and tensorflow 1.13.1.
- Install required libraries.
- Download ckpts.zip and unzip the file.
- The zip file contains model checkpoints VGG19 (converted from pytorch model zoo to tensorflow) and trained PatchSampler.
python main.py --image_path="data/parachute.png"
image_path
denotes the path to the image to explain.
Step 2. Check out the saved results in data/results/.
The examples of the PMI and IG maps are provided in data/results/parachute_K8_N8_S1.png