Start with Jetson Nano 16GB emmc module

Author : JTK
Date : 09-26-2022
Subject : Start with Jetson Nano 16GB emmc module

Good day, in this tutorial I’ll explain how to get a Jetson Nano 16GB emmc module working.
This is a way of many. At the end of this tutorial you will have access to Visual studio,
python 3, openCV and Detectnet v2. Hopefully you will succeed and you can enjoy the
power of the Jetson Nano.

Let’s get started

PART 1: Install SKD-M
PART 2: Make some Space!
PART 3: Installing
PART 4: Enjoy.

=============================

PART 1: Install SKD-M

https://www.waveshare.com/wiki/JETSON-NANO-DEV-KIT#Install_image_on_EMMC

Install Nvidia SDK- manager on a Ubuntu 18.xx PC
That will be your host, not a VM , just a PC.
Install only the Image, flash it…
Install Ubuntu, go to the therminal and go for part 2!

PART 2: Make some Space!

First check the Statics

$ df -h

Open the terminal and let’s go!

$ sudo apt update
$ sudo apt autoremove -y						
$ sudo apt clean
$ sudo apt-get remove --purge firefox* thunderbird* libreoffice* man-db libnvinfer-samples cuda-documentation-10-2 cuda-samples-10-2 libvisionworks-samples libopencv-samples -y

$ sudo apt-get autoremove

$ sudo rm -rf /usr/local/cuda/samples \

> /usr/src/cudnn_samples_* \
> /usr/src/tensorrt/data \
> /usr/src/tensorrt/samples \
> /usr/share/visionworks* ~/VisionWorks-SFM*Samples \
> /opt/nvidia/deepstream/deepstream*/samples



$ sudo rm -rf /usr/local/cuda/targets/aarch64-linux/lib/.a \
 > /usr/lib/aarch64-linux-gnu/libcudnn.a \
 > /usr/lib/aarch64-linux-gnu/libnvcaffe_parser*.a \
 > /usr/lib/aarch64-linux-gnu/libnvinfer*.a \
 > /usr/lib/aarch64-linux-gnu/libnvonnxparser*.a \
 > /usr/lib/aarch64-linux-gnu/libnvparsers*.a

$ sudo apt-get purge gnome-shell ubuntu-wallpapers-bionic light-themes chromium-browser* libvisionworks libvisionworks-sfm-dev -y
$ sudo apt-get autoremove -y
$ sudo apt clean -y

$ sudo rm -rf /usr/src/linux-headers-*
$ sudo apt purge cuda-repo-l4t-local libvisionworks-repo -y
$ sudo rm /etc/apt/sources.list.d/cuda*local /etc/apt/sources.list.d/visionworks*repo*

$ sudo apt clean

$ df -h

After this you should be have something like this: 3,9GB USE | 9,2GB FREE

PART 3: Installing

Jetpack;
Jetson-Inference;
Pip3;
OpenCV;
Numpy-Matplotlib;
Visual studio.

Open the terminal and go!

	$ sudo apt install nvidia-jetpack

INSTALL JETSON INFERENCE

$ sudo apt-get update
$ sudo apt-get install git cmake libpython3-dev python3-numpy
$ git clone --recursive https://github.com/dusty-nv/jetson-inference
$ cd jetson-inference
$ mkdir build
$ cd build

I only use Mobilenet v2 and skipped PyTorch

$ cmake ../    
$ make -j$(nproc)
$ sudo make install	
$ sudo ldconfig

PIP INSTALLL

$ sudo apt update
$ sudo apt install python3-pip
$ pip3 --version

=============================================#IINSTALL OPENCV 4.1.1!!!

$ sudo apt-get install python3-opencv
$ sudo apt-get remove python3-opencv

CHECK version:

$ python3
>>>import cv2 
>>>cv2.__version__

INSTALL VISUAL STUDIO , I Just love this IDE, not necessarily necessary

$ sudo apt-get update
$ cd Downloads
$ sudo apt-get install curl
$ curl -L https://github.com/toolboc/vscode/releases/download/1.32.3/code-oss_1.32.3-arm64.deb -o code-oss_1.32.3-arm64.deb
$ sudo dpkg -i code-oss_1.32.3-arm64.deb

After installing, create a folder where the codes are stored, link to VisualStudio FILE- Link folder. etc.

System settings Visual Studio

Go to EXTENSIONS, Type PYTHON, install PYTHON 3.

Lint is not necessary!

press: CTRL+SHIFT+P

And type in: select interpreter!

select it.

IINSTALL NUMPY,MATHPLOTLIB etc.

$ sudo apt-get install python3-matplotlib

Check the status

$ df -h

 12G Used, 1,9G Avail. 86% full

REBOOT the SYTEM

=====================

PART 4: ENJOY!

After the reboot, open an IDE and enjoy.
Have fun with your Jetson Nano!
  • JTK
1 Like

Nice! Thanks for your sharing with community!

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