With the release of JetPack 4.3, L4T 32.3.1 is now available for the NVIDIA Jetson Nano Developer Kit. Several of the JetsonHacksNano Github repositories on the JetsonHacksNano account have been updated to support this release.
Note that previous releases can be found in the ‘release’ section of each repository.
CSI-Camera
Simple example of using a MIPI-CSI(2) Camera (like the Raspberry Pi Version 2 camera) with the NVIDIA Jetson Nano Developer Kit. L4T 32.3.1 uses OpenCV 4.1.1 (previous versions were OpenCV 3.X), so the path names were changed to reflect the new library location.
buildKernelAndModules
This is a utility repository which aids in building the Linux kernel and modules. Several different repositories use this as the basis to build new kernel images. Note that the intended use is to use the repository scripts to download the kernel source files, compile the kernel, and compile the modules. Uses scripts/config to modify the .config file. Because you should be familiar with the Linux kernel make procedures, this is for advanced users only.
installLibrealsense
Starting with L4T 32.2.1 (JetPack 4.2.2) on the NVIDIA Jetsons and the Intel RealSense SDK version v2.23.0, it is now possible to do a simple install from a RealSense debian repository (i.e. apt-get install). Previous versions of this repository require building librealsense from source, and (possibly) rebuilding the Linux kernel.
The current recommendation from Intel is to use UVC for video input on the Jetson family. The UVC API in librealsense has been rewritten to better support this use case.
Now installs librealsense v2.31.0.
installRealSenseROS
Install the realsense-ros library on NVIDIA Jetson Nano Developer Kit. Installs RealSense ROS Version = 2.2.11, which expects a librealsense v2.31.0 installation.
4 Responses
Thank you SO MUCH! You ROCK! Happy New Year!
You are welcome. Happy New Year!
Hello! This is sort of unrelated, but I am wondering what your take is on connecting a PCIe to USB host card to the Jetson TX2. Is there a model you’ve found that works best?
I am currently connecting two realsense cameras and an arduino to the USB ports and it looks like there isn’t enough bandwidth, which is why I’m exploring this option.
Thanks!
I have not tried any personally. Please ask this question on the official NVIDIA Jetson forum where a large number of developers and NVIDIA engineers share their experience. The forum is here: https://devtalk.nvidia.com/default/board/188/jetson-tx2/