run.py

# Number of iterations to run.
ITERATIONS = 500

sess.run(tf.global_variables_initializer())
input_image = np.reshape(gen_image, ((1,) + gen_image.shape))
sess.run(model['input'].assign(input_image))
for it in range(ITERATIONS):
    sess.run(train_step)
    if it%50 == 0:
        # Print every 50 iteration.
        mixed_image = sess.run(model['input'])
        print('Iteration %d' % (it))
        print('cost: ', sess.run(total_loss))

        if not os.path.exists(OUTPUT_DIR):
            os.mkdir(OUTPUT_DIR)

        filename = 'output/%d.png' % (it)
        save_image(filename, mixed_image[0])
        
        final_image = recover_image(mixed_image[0]);
        imshow(final_image)
        plt.show()