f3f9e020119736920b5bf3adc91fd658e1910775,examples/mnist_denoising_autoencoder.py,,,#,33

Before Change

x_decoded = autoencoder.predict(x_test_noisy)

// Display the 1st 8 corrupted and denoised images
imgs = np.concatenate([x_test_noisy[:8], x_decoded[:8]])
imgs = imgs.reshape((4, 4, image_size, image_size))
imgs = np.vstack([np.hstack(i) for i in imgs])
plt.figure()

After Change

          "Corrupted Input: middle rows, "
          "Denoised Input:  third rows")
plt.imshow(imgs, interpolation="none", cmap="gray")
Image.fromarray(imgs).save("corrupted_and_denoised.png")
plt.show()

Instances