adversarial_autoencoder.py 文件源码

def generate_image_grid(sess, op):
    """
    Generates a grid of images by passing a set of numbers to the decoder and getting its output.
    :param sess: Tensorflow Session required to get the decoder output
    :param op: Operation that needs to be called inorder to get the decoder output
    :return: None, displays a matplotlib window with all the merged images.
    """
    x_points = np.arange(-10, 10, 1.5).astype(np.float32)
    y_points = np.arange(-10, 10, 1.5).astype(np.float32)

    nx, ny = len(x_points), len(y_points)
    plt.subplot()
    gs = gridspec.GridSpec(nx, ny, hspace=0.05, wspace=0.05)

    for i, g in enumerate(gs):
        z = np.concatenate(([x_points[int(i / ny)]], [y_points[int(i % nx)]]))
        z = np.reshape(z, (1, 2))
        x = sess.run(op, feed_dict={decoder_input: z})
        ax = plt.subplot(g)
        img = np.array(x.tolist()).reshape(28, 28)
        ax.imshow(img, cmap='gray')
        ax.set_xticks([])
        ax.set_yticks([])
        ax.set_aspect('auto')
    plt.show()