Yolov3 is very slow

[simone.rinaldi]

My first post, my first impression…

Just got the nano jetson, since long been using RPi’s, Odroids, and normal laptops etc etc like the rest of you I assume

I’m using Python for my video analyzing, I have no plans to change that. Managed to install OpenCV 4.1.1 with cuda support, took a long while but it works now

Running my script using yolov3, in an Odroid N2 takes around 10 sec to analyze a frame, in the nano jetson, I was hoping for a positive surprise, it takes approx 4 sec. In an old retired laptop running debian, the same frame takes just below a second (In RPi, just forget)

I’m also wondering if I’m doing something wrong. I’m not interested in running yolo tiny variants, the detection is much better with the heavy version

I’m listening, recommendation is TensorRT. But is the detection as good as in yolov3?

Otherwise, the nano jetson will be get a very early retirement

IMHO you need to renounce to use YOLOV3 on Jetson nano, is impossible to use.
You need to choose yolov3-tiny that with darknet could reach 17-18 fps at 416x416.

YoloV3 is wonderful but requires to many resources and in my opinion is required a good server with enough GPU (local or cloud).
Cosidering Jetson Nano consumption, it does a good job anyway.