上述函数改为读入一张图片

如果要将上述函数改为读入一张图片进行测试，可以将`test_files`改为一个包含单张图片路径的列表即可。修改后的代码如下：

def test(checkpoint_dir, style_name, test_img, if_adjust_brightness, img_size=[256,256]): 
    # tf.reset_default_graph()
    result_dir = 'results/'+style_name
    check_folder(result_dir)

    test_real = tf.placeholder(tf.float32, [1, None, None, 3], name='test')

    with tf.variable_scope("generator", reuse=False):
        test_generated = generator.G_net(test_real).fake

    saver = tf.train.Saver()

    gpu_options = tf.GPUOptions(allow_growth=True)
    with tf.Session(config=tf.ConfigProto(allow_soft_placement=True, gpu_options=gpu_options)) as sess:
        # tf.global_variables_initializer().run()
        # load model
        ckpt = tf.train.get_checkpoint_state(checkpoint_dir)  # checkpoint file information
        if ckpt and ckpt.model_checkpoint_path:
            ckpt_name = os.path.basename(ckpt.model_checkpoint_path)  # first line
            saver.restore(sess, os.path.join(checkpoint_dir, ckpt_name))
            print(" [*] Success to read {}".format(os.path.join(checkpoint_dir, ckpt_name)))
        else:
            print(" [*] Failed to find a checkpoint")
            return
        # stats_graph(tf.get_default_graph())

        begin = time.time()

        # print('Processing image: ' + test_img)
        sample_image = np.asarray(load_test_data(test_img, img_size))
        image_path = os.path.join(result_dir,'{0}'.format(os.path.basename(test_img)))
        fake_img = sess.run(test_generated, feed_dict = {test_real : sample_image})
        if if_adjust_brightness:
            save_images(fake_img, image_path, test_img)
        else:
            save_images(fake_img, image_path, None)

        end = time.time()
        print(f'test-time: {end-begin} s')

在调用该函数时，传入的第三个参数`test_img`应为单张图片的路径。