title: Tensor Flow Lite Model with Standard Tensorflow
body: <p>I am working on a Tensorflow simple app (would like to detect if people are in a captured image). </p>
  
  <p>I'm familiar with the python interface to Tensorflow. I see Tensorflow Lite has a different reduced format.</p>
  
  <p>I'm interested in using the model linked (for not wanting to spend time to create my own) in the Tensorflow Lite Examples in a traditional tensorflow python program with a PC Based GPU.</p>
  
  <p><a href="https://www.tensorflow.org/lite/models/image_classification/overview" rel="nofollow noreferrer">https://www.tensorflow.org/lite/models/image_classification/overview</a></p>
  
  <p>Is this possible?</p>
  
  <p>When I run the following code I receive</p>
  
  <pre><code>import tensorflow as tf
  def load_pb(path_to_pb):
      with tf.gfile.GFile(path_to_pb, "rb") as f:
          graph_def = tf.GraphDef()
          graph_def.ParseFromString(f.read())
       with tf.Graph().as_default() as graph:
          tf.import_graph_def(graph_def, name='')
          return graph
  
   load_pb('detect.tflite')
  </code></pre>
  
  <p>main.py:5: RuntimeWarning: Unexpected end-group tag: Not all data was converted
    graph_def.ParseFromString(f.read())</p>