How to run YOLOv8 inference using GPU on Jetson Nano

Autonomous Machines Jetson & Embedded Systems Jetson Nano
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I have created a virtual environment using python 3.8. But when I run yolov8 interference on Jetson using custom model, the inference is very slow, but showing 6-8ms. When i observed the gpu usage using jtop, it uses only some gpu. I also checked the torch cuda availability and it shows true…

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Dear @mjt7913,
Is it like a PyTorch based implementation? If so, can you convert to TRT model for better performance.

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TensorRT is already present in Jetson Nano but for python 3.6 but i’m using python 3.8… So do i have to build it for the same? and also I don’t know how to use TRT. If you know, could you briefly explain…Thank you…

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Dear @mjt7913,
If you have ONNX model. You can use trtexec tool in TensoRT to know the inference time of the model.

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