Part of MSc project. Involves using VGG16 pretrained on ImageNet
CLICK HERE to view the code and output
Using VGG16 pretrained on ImageNet for a new task by replacing the classifier at the top of the network
The jupyter notebook featured in this repo shows how to use VGG16 (pretrained on ImageNet) for a new classification task. It involves using a new dataset and replacing the classifier (the fully connected layers at top of the network) with a new classifier. The base of the network (convolutional base) is frozen and the new classifier is trained using the new dataset.
This repo also shows how to plot graphs using the training history information as well as creating a classification report using scikit-learn's classification_report function.