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 r1000	Raspberry Pi AI Kit
Get One Now 🖱️	Get One Now 🖱️

For Raspberry Pi 5

Raspberry Pi5 8GB	Raspberry Pi AI Kit
Get One Now 🖱️	Get One Now 🖱️

Run this project

CM4 Benchmark

For object detection please refer to the following wiki: yolov8_object_detection_on_recomputer_r1000_with_hailo_8l

For pose estimation Please refer to the following wiki: yolov8_pose_estimation_on_recomputer_r1000_with_hailo_8l

Pi5 Benchmark

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:

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:

Run Project

Run pose estimation

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

Run object detection

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 object detection with AI kit

bash run.sh object-detection-hailo

# run object detection without AI kit

bash run.sh object-detection

Result

Result

batchsize=1

batchsize=8

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