Jetson Nano Arch Linux for YOLO - Shell-Bash

Introduction

Jetson Nano is an affordable and powerful single-board computer designed for artificial intelligence (AI) and machine learning (ML) applications. It is based on the NVIDIA Jetson platform and comes with integrated graphics processing units (GPUs). YOLO (You Only Look Once) is an open-source deep learning framework that allows real-time object detection in images and videos. This tutorial will guide you through installing Arch Linux on Jetson Nano and setting up YOLO for object detection.

Prerequisites

Before proceeding with the installation and setup, make sure you have the following prerequisites:

• NVIDIA Jetson Nano board
• MicroSD card (minimum 16GB)
• MicroSD card reader
• Internet connection
• Basic knowledge of Linux commands

Steps

1. Download Arch Linux image

The first step is to download the Arch Linux image from the official website:

wget http://os.archlinuxarm.org/os/ArchLinuxARM-jetson-nano-latest.tar.gz

2. Extract image to microSD card

Next, extract the image to the microSD card using the following command:

sudo dd bs=4M if=ArchLinuxARM-jetson-nano-latest.tar.gz of=/dev/mmcblk0 status=progress && sync

3. Boot Jetson Nano with microSD card

Insert the microSD card into the Jetson Nano board and power it on. The board should boot from the microSD card and enter Arch Linux.

4. Connect to internet

Connect Jetson Nano to the internet using Ethernet cable or Wi-Fi.

ip link set eth0 up
dhcpcd eth0

5. Install required packages

Install the required packages for YOLO and other dependencies:

sudo pacman -S gcc cmake qt5-base opencv mesa-libglvnd protobuf python-pip nano wget unzip git

6. Install CUDA and cuDNN

Install CUDA and cuDNN for GPU acceleration:

sudo pacman -S cuda cudnn

7. Compile Darknet

Clone the Darknet repository and compile it:

git clone https://github.com/AlexeyAB/darknet.git
cd darknet
make -j$(nproc)

8. Test Darknet with YOLOv3

Download the pre-trained YOLOv3 weights and test the object detection:

wget https://pjreddie.com/media/files/yolov3.weights
./darknet detect cfg/yolov3.cfg yolov3.weights data/dog.jpg

9. Use YOLO in your own projects

You can now use YOLO in your own projects by importing the Darknet library and loading the pre-trained weights:

import darknet

net = darknet.load_net("cfg/yolov3.cfg", "yolov3.weights", 0)
meta = darknet.load_meta("cfg/coco.data")

detections = darknet.detect(net, meta, "data/dog.jpg")
print(detections)

Conclusion

This tutorial has introduced the steps to install Arch Linux on Jetson Nano and set up YOLO for object detection. With the power of Jetson Nano and YOLO, you can now develop your own AI and ML projects for various applications. Happy hacking!