Generative Adversarial Networks Projects

The generator network

The generator network is a CNN that takes a 100-dimensional vector z and generates an image with a dimension of (64, 64, 3). Let's implement the generator network in the Keras framework.

Perform the following steps to implement the generator network:

1. Start by creating the two input layers to the generator network:

latent_dims = 100num_classes = 6# Input layer for vector zinput_z_noise = Input(shape=(latent_dims, ))# Input layer for conditioning variableinput_label = Input(shape=(num_classes, ))

2. Next, concatenate the inputs along the channel dimension, as shown here:

x = concatenate([input_z_noise, input_label])

The preceding step will generate a concatenated tensor.

3. Next, add a dense (fully connected) block with ...