In this section, we are going to build a Java application for creating art. Before jumping into the code and application, let's look at the high-level description on how is it implemented. We will use transfer learning with the pre-trained VGG-16 architecture, trained on ImageNet dataset, which is a bunch of convolution layers in the following diagram:
Basically, as we go deeper, the depth of the third dimension increases, while the first two dimensions shrink in time.
At first, we are going to fit a content image as an input through a forward pass as shown in the following diagram. Then, we will gain the values of all activation layers along with the prediction. But for neural style transfer, we are not interested in the prediction, but only in the activation layers, because those layers are capturing the image features. The...
