Generative Adversarial Networks Projects

Training the CycleGAN

We have already covered the training objective function in the An Introduction to CycleGANs section. We have also created the respective Keras models for both networks. Training the CycleGAN is a multi-step process. We will perform the following steps to train the network:

1. Loading the dataset
2. Creating the generator and the discriminator networks
3. Training the network for a specified number of epochs
4. Plotting the losses
5. Generating new images

Let's define the essential variables before starting to train the network, as follows:

data_dir = "/Path/to/dataset/directory/*.*"batch_size = 1epochs = 500