Benchmarking-YOLOv8-on-Raspberry-PI-reComputer-r1000-and-AIkit-Hailo-8L

This repository demonstrates object detection model using YOLOv8 on a Raspberry Pi CM4 with Hailo Acceleration. The Raspberry Pi AI Kit enhances the performance of the Raspberry Pi and unlock its potential in artificial intelligence and machine learning applications, like smart retail, smart traffic and more. Although the Raspberry AI Kit is designed for Raspberry Pi 5, we have experimented it on our CM4-powered edge gateway. Excited about turning our edge device into an intelligent IoT gateway!

Hardware Preparation

reComputer R1000: Raspberry Pi CM4 Gateway, 4GB RAM, 32GB eMMC

Raspberry Pi AI Kit

Install Hailo-8L on the reComputer R1000

step 1. Install the Hailo-8L on the Raspberry Pi CM4

Step 2. Update system & Set pcie to gen3

sudo apt update
sudo apt full-upgrade
sudo raspi-config

Select option "6 Advanced Options":

Then select option "A8 PCIe Speed":

Choose "Yes" to enable PCIe Gen 3 mode:

Click "Finish" to exit.

Step 3. Install Hailo Software & Verify Installation

Install hailo-all and reboot

sudo apt install hailo-all
sudo reboot

Check that the Hailo software is installed correctly by running the following command:

hailortcli fw-control identify

The true result is as follows:

Check hailo hardware is installed correctly by running the following command:

lspci | grep Hailo

The true result is as follows:

Run this project

Run object detection on the Recomputer1000 without AI kit

Step 1. Install the repository

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

Step 2. The following command to run the object

cd Benchmarking-YOLOv8-on-Raspberry-PI-reComputer-r1000-and-AIkit-Hailo-8L
bash ./run.sh object-detection

Result

Run object detection on the Recomputer1000 with AI kit

Step 1. Install the repository

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

Step 2. The following command to run the object

cd Benchmarking-YOLOv8-on-Raspberry-PI-reComputer-r1000-and-AIkit-Hailo-8L
bash ./run.sh object-detection-hailo

Result

Run pose estimation on the Recomputer1000 without AI kit

Step 1. Install the repository

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

Step 2. The following command to run the object

cd Benchmarking-YOLOv8-on-Raspberry-PI-reComputer-r1000-and-AIkit-Hailo-8L
bash ./run.sh pose-estimation

Result

Run pose estimation on the Recomputer1000 with AI kit

Step 1. Install the repository

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

Step 2. The following command to run the object

cd Benchmarking-YOLOv8-on-Raspberry-PI-reComputer-r1000-and-AIkit-Hailo-8L
bash ./run.sh pose-estimation-hailo

Result

Results

Object	Without Hailo	With Hailo
YOLOV8 Object Detection	0.75FPS	29.5FPS
YOLOv8 Pose Estimation	0.5FPS	27FPS