Hands-On Deep Learning Algorithms with Python

Reconstructing the images

Reconstruct the images using our trained model:

reconstructed_images = model.predict(x_test)

First, let us plot the input images:

n = 7plt.figure(figsize=(20, 4))for i in range(n):     ax = plt.subplot(1, n, i+1)    plt.imshow(x_test[i].reshape(28, 28))    plt.gray()    ax.get_xaxis().set_visible(False)    ax.get_yaxis().set_visible(False)plt.show() 

The plot of the input images is as follows:

Now, we plot the reconstructed images:

n = 7plt.figure(figsize=(20, 4))for i in range(n):    ax = plt.subplot(2, n, i + n + 1)    plt.imshow(reconstructed_images[i].reshape(28, 28))    plt.gray()    ax.get_xaxis().set_visible(False) ax.get_yaxis().set_visible(False) ...