title: How to load a trained model saved by export_inference_graph.py?
body: <p>I'm folowing an example that uses tensorflow's 1.15.0 object detection API.
  The tutorial goes clearly on the following aspects:</p>
  
  <ul>
  <li>how to download a model</li>
  <li>how to load a custom database with .xml files, make .cvs files from them, and then .record files</li>
  <li>how to configure a training pipeline</li>
  <li>how to get tensorboard graphs</li>
  <li>how to train the net saving checkpoints (using model_main.py)</li>
  <li>how to export (save) the model (using export_inference_graph.py)</li>
  </ul>
  
  <p>What I have not been able to accomplish, however, is loading the saved model to use it.
  I tryed with <code>tf.saved_model.loader.load(sess, flags, export_dir</code>, but I get </p>
  
  <pre><code>INFO:tensorflow:Saver not created because there are no variables in the graph to restore.
  INFO:tensorflow:The specified SavedModel has no variables; no checkpoints were restored.
  </code></pre>
  
  <p>the folder given in <code>export_dir</code> has the following structure:</p>
  
  <pre><code>+dir
     +saved_model
        -saved_model.pb
     -model.ckpt.data-00000-of-00001
     -model.ckpt.index
     -checkpoint
     -frozen_inference_graph.pb
     -model.ckpt.meta
     -pipeline.config
  </code></pre>
  
  <p>My final goal here is to capture images with a camera, and feed them to the net for real time object detection.\
  As an in between step, now I just want to be able to feed a single picture and get the output. I was able to train the net, but now I can't use it.</p>
  
  <p>Thank you in advance.</p>