We are pleased to announce JetPack 4.5, a production release supporting Jetson AGX Xavier series, Jetson Xavier NX, Jetson TX2 series, Jetson TX1, and Jetson Nano.
JetPack 4.5 includes VPI 1.0, Security features including enhanced secure boot and support for full disk encryption, enhanced bootloader functionality, and a new way of flashing Jetson devices using NFS.
We will be hosting a webinar on Feb 9th for an in-depth overview of JetPack 4.5 features where we will also demo select features and answer any questions you may have. Please register here.
Learn how to implement computer vision and image processing pipelines using VPI by registering to the webinar we will be hosting on Feb 11th
Highlights of JetPack 4.5 are:
First Production release of Vision Programming Interface (VPI).
Thanks! I was eagerly waiting for this. One question. The webinar is 9 AM PT which translates to 2 AM local time for me. I know it will be recorded, but is it possible to have another session at an Asia friendly time?
Is the OpenCV 4.1.1 here built with CUDNN and CUDA enabled? I usually have to build the source package with these enabled and my understanding is OpenCV prior to 4.3 didn’t support past CUDNN v7
According to this page https://developer.nvidia.com/jetpack-sdk-45-archive 4.5 supports Cudnn 10.2. (above it says 8) Is possible to update 4.4.1 with just cudnn 10.2 while I wait for the 4.5 board support package to be completed for my carrier board?
This is great news! Regarding the notes section, do you mean to say that Jetpack 4.5 does not support the current containers listed on NGC? If so, what’s the dependency between the container and the Jetpack update? Will the containers go through a similar update each time Jetpack version gets updated?
Can you give a timeline when the containers will be updated?
@uersoy , The current containers listed on NGC is for JetPack 4.4.x. We will be releasing NGC containers in one or two business days for JetPack 4.5.
The present mechanism for containers we have has a depedency that it brings CUDA, cuDNN, TensorRT and othe components form host. We are working on changing this in future. So the depedency will be removed in future.
import torch
torch.version
‘1.7.0’
torch.cuda.is_available()
/usr/local/lib/python3.6/dist-packages/torch/cuda/init.py:52: UserWarning: CUDA initialization: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from Official Drivers | NVIDIA (Triggered internally at /media/nvidia/WD_NVME/PyTorch/JetPack_4.4.1/pytorch-v1.7.0/c10/cuda/CUDAFunctions.cpp:100.)
return torch._C._cuda_getDeviceCount() > 0
False
Hi @joey.su , no currently the containers have dependency on the root file system (which we are planning to remove going forward) and hence JP 4.5 base container need to be pulled on JetPack 4.5 only