Hi there!
I have followed the step by step wrote by @dusty_nv for training and inference of SSD300 model with Jetson Nano. Now I need do the same but with at least 512 resolution. I saw in the config file that there is a variable input_size = 300 but when i set it to 512 or more the program crash startting training phase.
I tryed modifying the specs from
specs = [
SSDSpec(38, 8, SSDBoxSizes(30, 60), [2]),
SSDSpec(19, 16, SSDBoxSizes(60, 111), [2, 3]),
SSDSpec(10, 32, SSDBoxSizes(111, 162), [2, 3]),
SSDSpec(5, 64, SSDBoxSizes(162, 213), [2, 3]),
SSDSpec(3, 100, SSDBoxSizes(213, 264), [2]),
SSDSpec(1, 300, SSDBoxSizes(264, 315), [2])
]
to
specs = [
SSDSpec(32, 16, SSDBoxSizes(20, 35), [2, 3]),
SSDSpec(16, 32, SSDBoxSizes(35, 50), [2, 3]),
SSDSpec(8, 64, SSDBoxSizes(50, 65), [2, 3]),
SSDSpec(4, 100, SSDBoxSizes(195, 240), [2, 3]),
SSDSpec(2, 150, SSDBoxSizes(240, 285), [2, 3]),
SSDSpec(1, 300, SSDBoxSizes(285, 512), [2, 3])
]
following this:
https://github.com/qfgaohao/pytorch-ssd/issues/128#issuecomment-688197358
I would like fix it in a correct way. Could we train the ssd with a biggest resolution? i need it for my client, is really important get it because i have little object to detect in a real time video (HD resolution). Thanks!