Generative Adversarial Networks Projects

The generator network

To implement the generator network, we need to create a Keras model and add the neural network layers. The steps required to implement the generator network are as follows:

1. Start by specifying the values for different hyperparameters:

z_size = 200gen_filters = [512, 256, 128, 64, 1]gen_kernel_sizes = [4, 4, 4, 4, 4]gen_strides = [1, 2, 2, 2, 2]gen_input_shape = (1, 1, 1, z_size)gen_activations = ['relu', 'relu', 'relu', 'relu', 'sigmoid']gen_convolutional_blocks = 5

2. Next, create an input layer to allow the network to take input. The input to the generator network is a vector sampled from a probabilistic latent space:

input_layer = Input(shape=gen_input_shape)

3. Then, add the first 3D transpose convolution (or 3D ...