The network I'm working on in TensorFlow produces a pixel-wise labeling result. TensorBoard is very helpful for viewing the data during training, but if I simply add 3 image_summarys I get an layout of the images something like:
o1
o2
o3
l1
l2
l3
p1
p2
p3
(where o# is the original image, l# is the ground truth labels, and p# is the predicted labels). What I would prefer to see is a layout like:
o1 l1 p1
o2 l2 p2
o3 l3 p3
As this would make comparing the results much easier. Does TensorBoard provide any convenient way of achieving this? Or would taking all the images, mapping non-RGB ones RGB, and simply concatenating them to make one long image be the best solution? Thank you much!