Good evening. I didn't write much, but I would like to leave it as a technical memo. This time, we will talk about the necessary items and initial setup of the new Jetson Nano (B01). Please see the official website for detailed specifications. [Jetson Nano Official URL] (https://www.nvidia.com/ja-jp/autonomous-machines/embedded-systems/jetson-nano/)
--Jetson Nano body (B01) * New model Purchase URL --AC adapter (5V / 4A) [Purchase URL] (https://www.amazon.co.jp/gp/product/B07SC6JSLL/ref=ppx_yo_dt_b_asin_title_o03_s00?ie=UTF8&psc=1) --MicroSD card (64GB) [Purchase URL] (https://www.amazon.co.jp/gp/product/B07DVJ86SS/ref=ppx_yo_dt_b_asin_title_o03_s01?ie=UTF8&psc=1)
※important point※ When using an AC adapter, a jumper pin is required for the old model, but it was originally included with the new model. However, since it is a new model, there is no guarantee that it will be included, so please make your own judgment. Also, the case was a little sized, or the holes weren't aligned, so I couldn't attach the wireless antenna well. Although it is a fan, it is used by placing it on top because it requires some ingenuity when screwing. When assembled, it will look like the one below.
The initial setup procedure before starting is described on the official website. Therefore, it is described briefly here. [Official Site Startup Guide (English Version)] (https://developer.nvidia.com/embedded/learn/get-started-jetson-nano-devkit)
You can check the JetPack version by running the following command
[email protected]:~$ cat /etc/nv_tegra_release R32 (release), REVISION: 3.1, GCID: 18186506, BOARD: t210ref, EABI: aarch64, DATE: Tue Dec 10 06:58:34 UTC 2019
This is difficult to understand, so the method to check with Python is described below.
git clone https://github.com/jetsonhacks/jetsonUtilities cd jetsonUtilities/ [email protected]:~/jetsonUtilities$ python jetsonInfo.py NVIDIA Jetson TX1 L4T 32.3.1 [ JetPack 4.3 ] Ubuntu 18.04.4 LTS Kernel Version: 4.9.140-tegra CUDA 10.0.326
The Jetson-based OS image (JetPack) includes the following so that applications can be executed immediately.
- OpenCV - cuDNN
For the time being, this is the end of the initial setup. Next time, I would like to describe the sample source and environment construction. If you have any questions, we are looking forward to hearing from you.