title: Tensorflow prediciton error, invalidArgumentError: assertion failed: [Unable to decode bytes as JPEG, PNG, GIF, or BMP]
body: <p>I trained a Tensorflow Ssd object-detection model using Google object-detection Api and i exported the trained model using the provided "export_inference_graph.py" script as "Saved_model.pb" file with "encoded_image_string_tensor" as input type, however when i tried to make prediction to the model, i got the following error:</p>
  
  <pre><code>tensorflow.python.framework.errors_impl.InvalidArgumentError: assertion failed: [Unable to decode bytes as JPEG, PNG, GIF, or BMP]
  </code></pre>
  
  <p>İ loaded the model into a graph as follow:</p>
  
  <pre><code>with tf.Session() as sess:
      tf.saved_model.loader.load(sess, [tf.saved_model.tag_constants.SERVING], saved_model_file)
      graph = tf.get_default_graph()
  </code></pre>
  
  <p>And made the prediction as follow:</p>
  
  <pre><code># Convert the image into base64 encoded string
  img = Image.open(IMAGE_PATH)    
  resized_img = img.resize((300, 300), Image.ANTIALIAS)
  binary_io = io.BytesIO()
  resized_img.save(binary_io, "JPEG")
  
  bytes_string_image = base64.b64encode(binary_io.getvalue()).decode("utf-8")
  
  # Define the input and output placeholder tensors
  input_tensor = graph.get_tensor_by_name('encoded_image_string_tensor:0')
  tensor_dict = {}
  for key in ['num_detections', 'detection_boxes', 'detection_scores', 'detection_classes']:
          tensor_name = key + ':0'
          tensor_dict[key] = graph.get_tensor_by_name(tensor_name)
  
  # Finally, do the prediciton
  output_dict = sess.run(tensor_dict, feed_dict={
                             input_tensor: bytes_string_image})
  </code></pre>