Question 1 is not very important.
(that’s mean I used the basic model provided DS5.0 DP version
path(resnet) = \opt\nvidia\deepstream\deepstream-5.0\samples\models\Primary_Detector_Nano
path(resnet) = \opt\nvidia\deepstream\deepstream-5.0\samples\models\tlt_pretrained_models)
below is peoplenet on DS 5.0 DP ver
I want to reduce the probability of recognizing chairs as people, as in the picture above.
and like my first question.
If I only want to use Person Class, can I reduce Layer to 18 levels and compress it to achieve more than 20 fps performance?
And it is the specification of host PC that I am thinking of, please confirm it.
cpu - amd 3900x
ram - 32gb
ssd - 500g
hdd - 2tb
gpu - (could you recommend a suitable specification for my retrain???) ex rtx2080 x2 or titan ~~blahblah