With the source GitHub - rbonghi/jetson_stats: 📊 Simple package for monitoring and control your NVIDIA Jetson [Xavier NX, Nano, AGX Xavier, TX1, TX2] I can see how much cpu and gpu I can use.
Also with source GitHub - theAIGuysCode/yolov4-deepsort: Object tracking implemented with YOLOv4, DeepSort, and TensorFlow. I running the Tracker with YOLOv4-Tiny
I was expecting higher performance. When I look at the GPU usage I can confirm it is working. But it works at low percentages.
Is there a way to get more out of the GPU? I want to take maximum advantage of Jetson AGX ORIN. I want to do projects such as object detection and object tracking with this device. I’m open to any resources you can suggest.
Best Regards, Hüseyin GÜLEK.