运行https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/image_retraining/label_image.py时脚本错误

Question

我试图通过引用下面的文档重新训练Inception的新类别的最后一层

• My : Windows 10 X64 Enterprise
• Python 3.6.2，Anaconda 4.4
• Tensorflow : 1.3.0 (仅CPU版本)

当我使用新的图像收集和完成培训，我使用以下推荐测试，但失败了！

(tensorflow13) C:\Users\James\Tensorflow\model-retrain\tensorflow-for-poets-2\scripts>python .\label_image.py --image c:\Users\James\Tensorflow\sample_img\Panda001.jpg --graph c:\Users\James\Tensorflow\model-retrain\tensorflow-for-poets-2\scripts\retrained_graph.pb --labels C:\Users\James\Tensorflow\model-retrain\tensorflow-for-poets-2\scripts\retrained_labels.txt

错误信息：

2017-09-01 09:27:46.902115: I C:\tf_jenkins\home\workspace\nightly-win\M\windows\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
Traceback (most recent call last):
  File ".\label_image.py", line 120, in <module>
    input_operation = graph.get_operation_by_name(input_name);
  File "C:\Users\James\AppData\Local\conda\conda\envs\tensorflow13\lib\site-packages\tensorflow\python\framework\ops.py", line 3225, in get_operation_by_name
    return self.as_graph_element(name, allow_tensor=False, allow_operation=True)
  File "C:\Users\James\AppData\Local\conda\conda\envs\tensorflow13\lib\site-packages\tensorflow\python\framework\ops.py", line 3097, in as_graph_element
    return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
  File "C:\Users\James\AppData\Local\conda\conda\envs\tensorflow13\lib\site-packages\tensorflow\python\framework\ops.py", line 3157, in _as_graph_element_locked
    "graph." % repr(name))
KeyError: "The name 'import/input' refers to an Operation not in the graph."

有人也有同样的问题吗？

Answer 1

由于某种原因，retrained_graph.pb没有脚本所期望的输入。它的构建可能与教程所期望的略有不同(特别是关于元图是如何导入的)。

Answer 2

更新到脚本的链接

这里的问题是您的输入/输出可能是错误的，脚本使用的是：

  input_name = "file_reader"
  output_name = "normalized"

如果您训练了这个模型，您可能需要找到您的输入/输出，因为它们可能是不同的。

我不知道找出这个问题的最佳方法，但是这段代码已经帮了我一个忙：

import tensorflow as tf
frozen='/tensorflow/mobilenets/mobilenet_v1_1.0_224.pb'
gf = tf.GraphDef()
gf.ParseFromString(open(frozen,'rb').read())
[n.name + '=>' +  n.op for n in gf.node if n.op in ( 'Softmax','Placeholder')]
[n.name + '=>' +  n.op for n in gf.node if n.op in ( 'Softmax','Mul')]