谷歌图像叙事功能

基于tensorflow 1.0实现im2txt。也可见博客地址：CSDN博客

预训练模型下载

由于本人实验环境相对较差，没有GPU，所以没有测试训练过程。因此下载了个预训练模型。 下载地址如下所示：https://drive.google.com/file/d/0Bw6m_66JSYLlRFVKQ2tGcUJaWjA/view

运行环境介绍

• Python 3.6
• Tensorflow >= 1.0.1
• model/im2txt

测试过程中填“坑”

（1） word_counts.txt文件的处理，需要将文件中的 b' str' ==> str，即把字符串的引号等全部去掉。

（2）修改预训练模型中的名称，由于预训练模型的名称不一致的问题，所以需要进行修改。

在具体代码修改中，添加一个函数来进行模型的修改和重新保存

由于版本不同，需要进行修改

def RenameCkpt(): vars_to_rename = { "lstm/BasicLSTMCell/Linear/Matrix": "lstm/basic_lstm_cell/weights", "lstm/BasicLSTMCell/Linear/Bias": "lstm/basic_lstm_cell/biases", } new_checkpoint_vars = {} reader = tf.train.NewCheckpointReader(FLAGS.checkpoint_path) for old_name in reader.get_variable_to_shape_map(): if old_name in vars_to_rename: new_name = vars_to_rename[old_name] else: new_name = old_name new_checkpoint_vars[new_name] = tf.Variable(reader.get_tensor(old_name))

init = tf.global_variables_initializer()
saver = tf.train.Saver(new_checkpoint_vars)

with tf.Session() as sess:
  sess.run(init)
  saver.save(sess, "/home/ndscbigdata/work/change/tf/gan/im2txt/ckpt/newmodel.ckpt-2000000")
print("checkpoint file rename successful... ")

训练结果：

图片放在data目录下:
![[image](./data/COCO_val2014_000000224477.jpg)]

图像 COCO_val2014_000000224477.jpg 标题是: 0) a man riding a wave on top of a surfboard . (概率=0.035672)

1. a person riding a surf board on a wave (概率=0.016238)
2. a man on a surfboard riding a wave . (概率=0.010146)

![[image](./data/ep271.jpg)]

图像 ep271.jpg 标题是: 0) a woman is standing next to a horse . (概率=0.000759)

1. a woman is standing next to a horse (概率=0.000647)
2. a woman is standing next to a brown horse . (概率=0.000384)

![[image](./data/dog.jpg)]

图像 dog.jpg 标题是: 0) a dog is eating a slice of pizza . (概率=0.000138)

1. a dog is eating a slice of pizza on a plate . (概率=0.000047)
2. a dog is sitting at a table with a pizza on it . (概率=0.000039)