read remote image files in tensorflow // url file reader

url_reader.py

import tensorflow as tf
from skimage import io
import time

N_THREADS = 64

BATCH_SIZE = 32
N_IMGS = 1000

random_img = 'url to load'

# Urls should be a list of urls. 
# You could make this function stateless by passing in a placeholder that is the 
# index of the url you want to load rather than auto incrementing it.
# io.imread doesn't engage the GIL so multiple requests can be made in parallel.
def url_example_producer(urls):
    def load_nth_url(n):
        return io.imread(urls[n])
    url_iter = tf.Variable(0, name='url_iter').count_up_to(len(urls))
    return tf.py_func(load_nth_url, [url_iter], stateful=True, Tout=[tf.uint8])
  
one_example = url_example_producer([random_img] * N_IMGS)

queue = tf.RandomShuffleQueue(capacity=500, min_after_dequeue=100, dtypes=tf.uint8, shapes=(300, 300, 3))
enq_op = queue.enqueue(one_example)
inputs = queue.dequeue_many(BATCH_SIZE)
qr = tf.train.QueueRunner(queue, [enq_op] * N_THREADS)

with tf.Session() as sess:
    tf.initialize_all_variables().run()
    coord = tf.train.Coordinator()
    enqueue_threads = qr.create_threads(sess, coord=coord, start=True)
    t = time.time()
    try:
        while not coord.should_stop():
            # Load images
            images = sess.run(inputs)
            print len(images), images[0].shape

    except tf.errors.OutOfRangeError:
        print('Done loading -- limit reached', 'Took:', time.time() - t)
    finally:
        # When done, ask the threads to stop.
        coord.request_stop()
    # Wait for threads to finish.
    coord.join(enqueue_threads)

hi , i want to read url image directly ,because we will use this in tensor serving,but ,the serving does not support tf.py_func