Neural Networks with Keras Cookbook

How to do it...

We'll code up the strategy that we laid out in the Getting ready section, as follows (The code file is available as Face_generation.ipynb in GitHub):

1. Generate the first image from random noise (note that we'll continue from step 6 in Face generation using a Deep Convolutional GAN section):

gen_noise = np.random.normal(0, 1, (1, 100))syntetic_images = Generator.predict(gen_noise)plt.imshow(deprocess(syntetic_images)[0])plt.axis('off')

The generated image looks as follows:

2. Generate the second image from random noise:

gen_noise2 = np.random.normal(0, 1, (1, 100))syntetic_images = Generator.predict(gen_noise2)plt.imshow(deprocess(syntetic_images)[0]) ...