Generative Adversarial Networks Projects

Training the generator network

The steps given in this section show how to train the generator network. This is a continuation of the last series of steps:

1. Again, sample a batch of high-resolution and low-resolution images and normalize them:

    high_resolution_images, low_resolution_images = sample_images(data_dir=data_dir,                         batch_size=batch_size,low_resolution_shape=low_resolution_shape,                                                                                    high_resolution_shape=high_resolution_shape)        # Normalize images    high_resolution_images = high_resolution_images / 127.5 - 1.    low_resolution_images = low_resolution_images / 127.5 - 1.

2. Use the VGG19 network to extract feature maps (internal representations) of real high-resolution images:

    image_features = vgg.predict(high_resolution_images)

3. Finally, ...