如何通过tf.image_summary查看多个图像

问题 - TensorBoard只显示一个图像

灵感来自于 如何在Tensorflow中可视化cnn中的权重(变量)？

这是代码:

# --- image reader ---
# - rsq: random shuffle queue with [fn l] pairs 
def img_reader_jpg(rsq):
    fn, label  = rsq.dequeue()
    img_b = tf.read_file(fn)
    img_u = tf.image.decode_jpeg(img_b, channels=3) 
    img_f = tf.cast(img_u, tf.float32)  
    img_4 = tf.expand_dims(img_f,0)
    return img_4, label


# filenames and labels are pre-loaded
fv = tf.constant(fnames)
lv = tf.constant(ohl)

rsq    = tf.RandomShuffleQueue(len(fnames), 0, [tf.string, tf.float32])
do_enq = rsq.enqueue_many([fv, lv])

# reading_op 
image, label   = img_reader_jpg(rsq)

# test: some op
im_t     = tf.placeholder(tf.float32, shape=[None,30,30,3], name='img_tensor')
lab_t    = tf.placeholder(tf.float32, shape=[None,2],       name='lab_tensor')
some_op  = tf.add(im_t,im_t) 
ims_op   = tf.image_summary("img", im_t)

# service ops
init_op    = tf.initialize_all_variables()

#  run it
with tf.Session() as sess:

    summary_writer = tf.train.SummaryWriter(summ_dir, graph_def=sess.graph_def)
    print 'log at:', summ_dir

    sess.run(init_op)
    sess.run(do_enq)
    print "rsq.size:", rsq.size().eval()

    for i in xrange(5):
        print "\ni:",i

        img_i, lab_i = sess.run([image, label]) # read image - right?
        print "I:", img_i.shape , " L:", lab_i

        feed_dict = {
            im_t: img_i
        }

        img2 = sess.run([some_op], feed_dict = feed_dict)

        # now summary part
        imss = sess.run(ims_op, feed_dict = feed_dict)
        #print "imss",imss
        summary_writer.add_summary(imss,i) 

    print "rsq.size:", rsq.size().eval()
    summary_writer.close()

print 'ok'

log at: /mnt/code/test_00/log/2016-01-09 17:10:37
rsq.size: 1225

i: 0
I: (1, 30, 30, 3)  L: [ 1.  0.]

i: 1
I: (1, 30, 30, 3)  L: [ 1.  0.]

i: 2
I: (1, 30, 30, 3)  L: [ 0.  1.]

i: 3
I: (1, 30, 30, 3)  L: [ 0.  1.]

i: 4
I: (1, 30, 30, 3)  L: [ 0.  1.]
rsq.size: 1220
ok