f2073333b710a340403843763ba60eb1e6699916,examples/data_process/tutorial_tfrecord2.py,,,#,81

Before Change

    coord = tf.train.Coordinator()
    threads = tf.train.start_queue_runners(sess=sess, coord=coord)

    for i in range(3):  // number of mini-batch (step)
        print("Step %d" % i)
        val, l = sess.run([img_batch, label_batch])
        print(val.shape, l)
        tl.visualize.images2d(val, second=1, saveable=False, name="batch" + str(i), dtype=np.uint8, fig_idx=2020121)
        tl.vis.save_images(val, [2, 2], "_batch_%d.png" % i)

    coord.request_stop()
    coord.join(threads)
    sess.close()

After Change

        label_batch = tf.cast(features["label"], tf.int32)
        yield img_batch, label_batch

img_batch, label_batch = next(read_and_decode("train.tfrecords"))
print("img_batch   : %s" % img_batch.shape)
print("label_batch : %s" % label_batch.shape)

i = 0

Instances