How can I convert TFRecords into numpy arrays?

Question

The main idea is to convert TFRecords into numpy arrays. Assume that the TFRecord stores images. Specifically:

1. Read a TFRecord File and convert each image into

Answer 1

Oops, it was a silly mistake on my part. I used a string_input_producer but forgot to run the queue_runners.

with tf.Session() as sess:
  filename_queue = tf.train.string_input_producer(["../data/svhn/svhn_train.tfrecords"])
  image, label, height, width, depth = read_and_decode(filename_queue)
  image = tf.reshape(image, tf.pack([height, width, 3]))
  image.set_shape([32,32,3])
  init_op = tf.initialize_all_variables()
  sess.run(init_op)
  coord = tf.train.Coordinator()
  threads = tf.train.start_queue_runners(coord=coord)
  for i in range(1000):
    example, l = sess.run([image, label])
    print (example,l)
  coord.request_stop()
  coord.join(threads)