QuickDraw_noisy_classifier.py 文件源码

def plot_compare(x_test, decoded_imgs, filename):
    n = 10
    plt.figure(figsize=(2*n, 4))
    for i in range(n):
        # display original
        ax = plt.subplot(2, 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)

        # display reconstruction
        ax = plt.subplot(2, n, i + 1 + n)
        plt.imshow(decoded_imgs[i].reshape(28, 28))
        plt.gray()
        ax.get_xaxis().set_visible(False)
        ax.get_yaxis().set_visible(False)

    if 1:
        pylab.savefig(filename, bbox_inches='tight')
    else:
        plt.show()

# plot_img: plots greyscale image