Like any other GAN, training the pix2pix network is a two-step process. In the first step, we train the discriminator network. In the second step, we train the adversarial network, which eventually trains the generator network. Let's start training the network.
Perform the following steps to train an SRGAN network:
- Start by defining the hyperparameters that are required for training:
epochs = 500num_images_per_epoch = 400batch_size = 1img_width = 256img_height = 256num_channels = 1input_img_dim = (256, 256, 1)patch_dim = (256, 256)# Specify dataset directory pathdataset_dir = "pix2pix-keras/pix2pix/data/facades_bw"
- Next, define the common optimizer, shown as follows:
common_optimizer = Adam(lr=1E-4, beta_1 ...
