title: Tensorflow: Use tf.parse_example for jpeg batches
body: <p>I just stumbled over this question:
  <a href="https://stackoverflow.com/questions/37151895/tensorflow-read-all-examples-from-a-tfrecords-at-once?rq=1">TensorFlow - Read all examples from a TFRecords at once?</a></p>
  
  <p>And the first answer suggest using tf.parse_example instead of parsing single examples because that seems to be faster. But the code provided is not complete and I don't know how I can use that. If I batch and then use parse_example I will get a batch of features. That means I need to unpack that batch in order to decode the jpegs? The code from the answer is:</p>
  
  <pre><code>reader = tf.TFRecordReader()
   _, serialized_example = reader.read(filename_queue)
   features = tf.parse_single_example(serialized_example, features={
        image/center': tf.VarLenFeature(tf.string),
    })
   image = features['image/center']
   image_decoded = tf.image.decode_jpeg(image.values[0], channels=3)
   return image_decoded
  </code></pre>
  
  <p>And suggest switching to:</p>
  
  <pre><code>batch = tf.train.batch([serialized_example], num_examples, capacity=num_examples)
  parsed_examples = tf.parse_example(batch, feature_spec)
  </code></pre>
  
  <p>But how can I now decode those parsed_examples?</p>