To keep things interesting, we will conclude our smile detector experiments and actually use a pre-trained, very deep CNN to demonstrate our leopard example. We also use the Keras vis, which is a great higher-level toolkit to visualize and debug CNNs built on Keras. You can install this package using the pip package manager:
Here, we import the ResNet50 CNN architecture with pretrained weights for the ImageNet dataset. We encourage you to explore other models stored in Keras as well, accessible through keras.applications. We also switch out the Softmax activation for the linear activation function in the last layer of this network using utils.apply_modifications, which rebuilds the network graph to help us visualize the saliency of maps better.
ResNet50 was first introduced as the ILSVRC competition and won first place in 2015. It does...
