QR Code Detection

Introduction

🛒 I. Retail's Efficiency Crisis & AI-Powered Transformation Opportunity

In smart retail scenarios, AI cameras combined with the QR-Code detection technology of the lightweight YOLOv8n model are gradually replacing traditional barcode scanning devices to achieve automation and intelligence in product identification and settlement.

🤖 II. Arducam's Edge AI Revolution: SONY IMX500-Driven Retail Ecosystem

Core Solution:

Arducam's embedded vision systems deploy SONY IMX500-powered smart cameras with integrated YOLOv8n models for real-time QR detection. This architecture enables fast item identification during checkout while simultaneously verifying product authenticity.

SONY IMX500 Ecosystem Advantage:

First intelligent vision sensor with integrated AI processing On-sensor machine learning eliminates cloud dependency 12.3MP resolution with ultra-low 100mW power consumption

⚡ III. Advantages of Arducam AI Camera Solution

By deploying cameras with local AI reasoning capabilities, the system can identify product QR codes within milliseconds, greatly improving cash register efficiency, reducing manual operations, and lowering operation and maintenance costs. This solution is suitable for scenarios such as unmanned convenience stores and self-service checkout counters, providing a cost-effective, easy-to-deploy, and scalable overall solution for smart retail.

AI Model Dataset

Arducam Pre-trained QR Code detection dataset

AI Model Example

Hardware Preparation

The following demo is based on Arducam IMX500 Raspberry Pi 5 All-in-one AI Camera Kit:

Product Image	SKU	Resolution	Sensor	Lens Mount	Focus Type	Field of View(DxHxV)	IR Sensitivity	Power Requirements	Operating Temp.
	B0540	12.3MP	SONY IMX500	Stock Lens	Fixed Focs	78±3°(D)×66±3°(H)×52.3±3°(V)	Integral 650nm IR Filter	Max 7.5W	0°C to 50°C

Software Preparation

Export IMX500 AI model compressed package

IMX500 AI Model Package-QR Code Detection

Deployment

Start the IMX500 Raspberry Pi All-in-One and run the following code to install the environment

sudo apt update && sudo apt full-upgrade
sudo apt install imx500-all imx500-tools
sudo apt install python3-opencv python3-munkres

Use the following command to package the IMX500 model into rpk (note to replace the path example below with the actual path)

imx500-package -i <path to packerOut.zip> -o <output folder>

Download and install picamera2, and run the startup script (note to replace the actual rpk model path)

git clone https://github.com/raspberrypi/picamera2
cd picamera2
pip install -e .  --break-system-packages
cd examples/imx500
python imx500_object_detection_demo.py --model ~/dev_workspace/output/network.rpk --fps 17 --bbox-normalization --ignore-dash-labels --bbox-order xy --labels ~/dev_workspace/qrcode.txt