Hello! I've found a performance issue in /object_detection/eval_util.py: sess = tf.Session(master, graph=tf.get_default_graph())(here) is defined in the function run_checkpoint_once(here) which is repeatedly called in the loop while True(here).
tf.Session being defined repeatedly could lead to incremental overhead. If you define tf.Session out of the loop and pass tf.Session as a parameter to the loop, your program would be much more efficient. Here is the Stack Overflow post to support it.
Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.
Hello! I've found a performance issue in /object_detection/eval_util.py:
sess = tf.Session(master, graph=tf.get_default_graph())
(here) is defined in the functionrun_checkpoint_once
(here) which is repeatedly called in the loopwhile True
(here).tf.Session
being defined repeatedly could lead to incremental overhead. If you definetf.Session
out of the loop and passtf.Session
as a parameter to the loop, your program would be much more efficient. Here is the Stack Overflow post to support it.Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.