YOLOv5 performance on Jetson Xavier AGX


I am working on Nvidia Jetson Xavier AGX.
While using https://github.com/ultralytics/yolov5 repository as is, latest version with yolov5s model.
When running python3 detect.py --source 0 --img-size 640 inference time is 0.040s.
When running python3 detect.py --source 0 --img-size 256 inference time is 0.025s.

I would be happy to know if those results seem reasonable or am I missing something**

Additional context

OS: Ubuntu 18.04 (JetPack)
OPERATION MODE: MAXN (Maximum performance)
Python: 3.6
Pytorch: 1.6.0 ( according to this topic )
CUDA: 10
Camera: 120 FPS camera (so I wish to achieve this inference FPS)



We don’t have a performance result for YOLOv5.
Here are some result for YOLOv3, you can compare it based on the complexity of the model: