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import numpy as np | |
from keras.datasets import fashion_mnist | |
from image_helper import ImageHelper | |
from dcgan import DCGAN | |
(X, _), (_, _) = fashion_mnist.load_data() | |
X_train = X / 127.5 - 1. | |
X_train = np.expand_dims(X_train, axis=3) | |
image_helper = ImageHelper() | |
generative_advarsial_network = DCGAN(X_train[0].shape, 100, image_helper, 1) | |
generative_advarsial_network.train(20000, X_train, batch_size=32) |
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