I trained my own FCN_resnet18 segmentation network for a cityskape like dataset.
The model is working, but I have huge performance issue. Network FPS is 30, which is really good, but I am only able to make 4 inference loop per second.
According to profile information, all the time is used to post process the inference result in segnet function.
My code is strongly inspired by the segmentation training example from jetson.inference. My understanding was that the example provided with various tools like segnet.py were generated using this tool. Obviously not.
Provided models like fcn-resnet18-cityscapes-512x256 have an output layer of 16x8xnum_class, were default FCN_resnet have output layers with the same size as input one (512x256xnum_class in my case).
Could we have access to the code used to generate this models structure ?
Does someone know which transformation can be done to reduce output layer size ?
Thanks for your help & merry Xmas to you