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 |
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For Raspberry Pi 5
Raspberry Pi5 8GB | Raspberry Pi AI Kit |
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Run this project
- CM4 Benchmark
- Pi5 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
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
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
- 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 pose estimation with AI kit
bash run.sh pose-estimation-hailo
# run pose estimation without AI kit
bash run.sh pose-estimation
Result
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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