title: Tensorflow Object detection API: Print detected class as output to terminal
body: <p>I have a simple question, but I can't figure out how to do it. I am using the TF Object detection API to detect images, it is working fine and given an image it will draw the bounding box with a label and confidence score of what class it thinks its detected. My question is how can I print the detected class (as a string) and the score to terminal i.e not just on the image but as an output to the terminal too.</p>
  
  <p>Below is the code responsible for the image detection</p>
  
  <pre><code>with detection_graph.as_default():
    with tf.Session(graph=detection_graph) as sess:
      for image_path in TEST_IMAGE_PATHS:
        image = Image.open(image_path)
        # the array based representation of the image will be used later in order to prepare the
        # result image with boxes and labels on it.
        image_np = load_image_into_numpy_array(image)
        # Expand dimensions since the model expects images to have shape: [1, None, None, 3]
        image_np_expanded = np.expand_dims(image_np, axis=0)
        image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
        # Each box represents a part of the image where a particular object was detected.
        boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
        # Each score represent how level of confidence for each of the objects.
        # Score is shown on the result image, together with the class label.
        scores = detection_graph.get_tensor_by_name('detection_scores:0')
        classes = detection_graph.get_tensor_by_name('detection_classes:0')
        num_detections = detection_graph.get_tensor_by_name('num_detections:0')
        # Actual detection.
        (boxes, scores, classes, num_detections) = sess.run(
            [boxes, scores, classes, num_detections],
            feed_dict={image_tensor: image_np_expanded})
        # Visualization of the results of a detection.
        vis_util.visualize_boxes_and_labels_on_image_array(
            image_np,
            np.squeeze(boxes),
            np.squeeze(classes).astype(np.int32),
            np.squeeze(scores),
            category_index,
            use_normalized_coordinates=True,
            line_thickness=8, min_score_thresh=.2)
        plt.figure(figsize=IMAGE_SIZE)
        plt.imshow(image_np)
        plt.show()
  </code></pre>
  
  <p>Thanks in advance, first post on Stack Overflow so please go easy on me</p>