This project is about analyzing what goes under the hood for pruning.

• Dataset: PASCAL-VOC2012 (cat,dog,horse,person)
• Image preprocessing: Resized to 128x128
• Model: VGG16-variant

Model training & pruning performed on Google Colaboratory.
Pruning is performed using a corrected version of Keras Surgeon.
Grad-CAM from Keras-GradCAM.
Code to read PASCAL-VOC data using modified version of pascal-voc-python.

Dataset images and GradCAM images (incl. GIFs) can be found here: GDrive link

iPython notebooks are organised into:
01 image loading & preprocessing
02 channel pruning & tuning
03 Grad-CAM (channel pruning)
04 layer pruning & tuning
05 Grad-CAM (layer pruning)
06 images where class prediction change the most