In this recipe, we look at the most basic GAN network for the Fashion-MNIST dataset.
Fashion-MNIST is a dataset of Zalando article images consisting of a training set of 60,000 examples; it also contains a test set of 10,000 examples. Each example is a 28 x 28 grayscale image, associated with a label from 10 classes.
Here are some example images from Fashion-MNIST:
Fashion MNIST is directly available in Keras.
Create a class called GAN. Import the relevant classes and initialize the variables:
from __future__ import print_function, division from keras.datasets import fashion_mnist from keras.layers import Input, Dense, Reshape, Flatten, Dropout from keras.layers import BatchNormalization, Activation, ZeroPadding2D from keras.layers.advanced_activations import LeakyReLU from keras.layers.convolutional import UpSampling2D, Conv2D from keras.models import Sequential, Model from keras.optimizers import Adam import matplotlib.pyplot as plt import sys import numpy as np GAN...