title: How to interpret TFLite output tensor
body: <p>I am executing a TFLite model on python in order to make predictions based on input data. The model has been trained on AutoML-Google-API, then I downloaded its TFLite model. I used tf.lite.Interpreter to load the model and run an inference as follows</p>
  
  <pre><code>input_details = interpreter.get_input_details();print(input_details )
  output_details = interpreter.get_output_details();print(output_details )
  //...preparing input_data
  interpreter.set_tensor(input_details[0]['index'], input_data)
  interpreter.invoke()
  output_data = interpreter.get_tensor(output_details[0]['index']);print(output_data )
  </code></pre>
  
  <p>The results are as follows:</p>
  
  <pre><code>input_details: 
  [{'name': 'image',
    'index': 0,
    'shape': array([  1, 224, 224,   3]),
    'dtype': numpy.uint8,
    'quantization': (0.007874015718698502, 128)}]
  output_details: 
  [{'name': 'scores',
    'index': 173,
    'shape': array([ 1, 10]),
    'dtype': numpy.uint8,
    'quantization': (0.00390625, 0)}]
  output_data : 
  array([[ 34, 100,  67,  14,  15,  24,  21,  18,  25,  37]], dtype=uint8)
  </code></pre>
  
  <p>The <code>output_data</code> has some integer numbers, is it true to say that "the index of its largest number corresponds to the predicted label", and how can I convert those numbers to probability? </p>