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Benchmark on RPi5 and CM4 running yolov8s with rpi ai kit

Introduction​

YOLOv8 (You Only Look Once version 8) is the popular most YOLO series of real-time pose estimation and object de tection models. It builds upon the strengths of its predecessors by introducing several advancements in speed, accuracy, and flexibility. The Raspberry-pi-AI-kit is used to accelerate inference speed, featuring a 13 tera-operations per second (TOPS) neural network inference accelerator built around the Hailo-8L chip.

This wiki showcases benchmarking of YOLOv8s for pose estimation and object detection on Raspberry Pi 5 and Raspberry Pi Compute Module 4. All tests utilize the same model (YOLOv8s), quantized to int8, with an input size of 640x640 resolution, batch size set to 1, and input from the same video at 240 FPS.

Prepare Hardware​

For CM4​

reComputer r1000Raspberry Pi AI Kit
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Get One Now 🖱️

For Raspberry Pi 5​

Raspberry Pi5 8GBRaspberry Pi AI Kit
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Get One Now 🖱️

Run this project​

Install AI kit on RPi5​

Please refer to this

Install Hailo Software & Verify Installation​

update the system:​

sudo apt update
sudo apt full-upgrade

Set pcie to gen2/gen3(gen3 is faster than gen2):​

Add following text to /boot/firmware/config.txt

#Enable the PCIe external connector

dtparam=pciex1

#Force Gen 3.0 speeds

dtparam=pciex1_gen=3

note

If you want to use gen2,please comment dtparam=pciex1_gen=3

Install hailo-all and reboot:​

Open terminal on the Raspberry Pi5, and input command as follows to install Hailo software.

sudo apt install hailo-all
sudo reboot

Check Software and Hardware:​

Open terminal on the Raspberry Pi5, and input command as follows to check if hailo-all have been installed.

hailortcli fw-control identify

The right result show as bellow:

pir

Open terminal on the Raspberry Pi5, and input command as follows to check if hailo-8L have been connected.

lspci | grep Hailo

The right result show as bellow:

pir

Run Project​

Install Project​

git clone https://github.com/Seeed-Projects/Benchmarking-YOLOv8-on-Raspberry-PI-reComputer-r1000-and-AIkit-Hailo-8L.git
cd Benchmarking-YOLOv8-on-Raspberry-PI-reComputer-r1000-and-AIkit-Hailo-8L

Run the project​

# run pose estimation with AI kit

bash run.sh pose-estimation-hailo

# run pose estimation without AI kit

bash run.sh pose-estimation

Result​

Result​

pir

pir

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