Keras implementation of CycleGAN

As discussed earlier in this chapter in the An Introduction to CycleGANs section, CycleGANs have two network architectures, a generator and a discriminator network. In this section, we will write the implementation for all the networks.

Before starting to write the implementations, however, create a Python file, main.py, and import the essential modules, as follows:

from glob import glob
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from keras import Input, Model
from keras.layers import Conv2D, BatchNormalization, Activation, Add, Conv2DTranspose, \
    ZeroPadding2D, LeakyReLU
from keras.optimizers import Adam
from keras_contrib.layers import InstanceNormalization
from scipy.misc import imread, imresize

The generator network

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