How to use image_summary to view images from different batches in Tensorflow?

Question

I am curious about how image_summary works. There is a parameter called max_images, which controls how many images would be shown. However it seems the summary only displays

Answer 1

I was able to solve this by creating a new image_summary op for each batch. i.e. I went from something that looked like:

train_writer = tf.train.SummaryWriter('summary_dir')
img = tf.image_summary("fooImage", img_data)
for i in range(N_BATCHES):
  summary, _ = sess.run([img, train_step])
  train_writer.add_summary(summary, i)

(Which, frustratingly, was not doing what I expected.) To...

train_writer = tf.train.SummaryWriter('summary_dir')
for i in range(N_BATCHES):
  # Images are sorted in lexicographic order, so zero-pad the name
  img = tf.image_summary("fooImage{:06d}".format(i), img_data)
  summary, _ = sess.run([img, train_step])
  train_writer.add_summary(summary)