I am using the Jetson Nano 4GB that was flashed with the following installed:
nvidia-l4t-core 32.6.1-20210726122000 (which i assume is Jetpack 4.6 or 4.6.1?)
CUDA 10.2
cudnn 8.2.1
For a real time detection project, I am implementing a Machine Learning model that is a .h5 file, and accessing the CSI camera using GStreamer enabled OpenCV. This is a very heavy code so I want to use the GPU. I have tried using Tensorflow-cpu on my code but I am literally getting a new frame every 2 seconds which is crazy slow. Im sure using the GPU would be much better than using the CPU for this case.
How can I can Tensorflow to recognize my GPU so that I can use it for my detection code? What version is compatible with CUDA 10.2 and cudnn 8.2.1 that comes installed on the Jetson Nano?
Official TensorFlow for Jetson Nano! has verified steps on different jetpack release. If you don’t have any dependency on jetpack version, you may consider upgrading.
When I flashed the OS onto the Jetson Nano, I was only given the default 4.6 download option when following the steps on Nvidia’s page. I could not find a 4.6.3 version to download.
I tried reflashing again but when i turned on the Jetson, it is as if nothing happened and I didnt re-flash the card. Would the 16GB eMMC have something to do with the fact that the re-flash had no virtually no effect on the system? @SivaRamaKrishnaNV