Raspberry pi5 Yolov8 Object Detection
YOLOv8 from Ultralytics
Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost performance and flexibility. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks.
Raspberry pi 5
Specification- Broadcom BCM2712 2.4GHz quad-core 64-bit Arm Cortex-A76 CPU, with cryptography extensions, 512KB per-core L2 caches and a 2MB shared L3 cache
- VideoCore VII GPU, supporting OpenGL ES 3.1, Vulkan 1.2
- Dual 4Kp60 HDMI® display output with HDR support
- 4Kp60 HEVC decoder
- LPDDR4X-4267 SDRAM (4GB and 8GB SKUs available at launch)
- Dual-band 802.11ac Wi-Fi®
- Bluetooth 5.0 / Bluetooth Low Energy (BLE)
- microSD card slot, with support for high-speed SDR104 mode
- 2 × USB 3.0 ports, supporting simultaneous 5Gbps operation
- 2 × USB 2.0 ports
- Gigabit Ethernet, with PoE+ support (requires separate PoE+ HAT)
- 2 × 4-lane MIPI camera/display transceivers
- PCIe 2.0 x1 interface for fast peripherals (requires separate M.2 HAT or other adapter)
- 5V/5A DC power via USB-C, with Power Delivery support
- Raspberry Pi standard 40-pin header
- Real-time clock (RTC), powered from external battery
- Power button
Raspberry Pi 3, 4, and 5 compare
| Feature | Raspberry Pi 3 | Raspberry Pi 4 | Raspberry Pi 5 |
|---|---|---|---|
| CPU | 1.2GHz Quad-Core ARM Cortex-A53 | 1.5GHz Quad-core 64-bit ARM Cortex-A72 | 2.4GHz Quad-core 64-bit Arm Cortex-A76 |
| RAM | 1GB LPDDR2 | 2GB, 4GB or 8GB LPDDR4 | Details not yet available |
| USB Ports | 4 x USB 2.0 | 2 x USB 2.0, 2 x USB 3.0 | 2 x USB 3.0, 2 x USB 2.0 |
| Network | Ethernet & Wi-Fi 802.11n | Gigabit Ethernet & Wi-Fi 802.11ac | Gigabit Ethernet with PoE+ support, Dual-band 802.11ac Wi-Fi® |
| Performance | Slower, may require lighter YOLO models | Faster, can run complex YOLO models | Details not yet available |
| Power Requirement | 2.5A power supply | 3.0A USB-C power supply | Details not yet available |
| Official Documentation | Link | Link | Link |
Raspberry pi OS
Install Library
Pip install the ultralytics package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.
pip install ultralytics
Run Test Image with Command Line
YOLOv8 may be used directly in the Command Line Interface (CLI) with a yolo command:
yolo predict model=yolov8n.pt source='https://ultralytics.com/images/bus.jpg'
yolo predict model=yolov8n.pt source=/home/pi/Video/your_video.mp4 show=True
Reference
Quick Start Guide: Raspberry Pi and Pi Camera with YOLOv5 and YOLOv8
https://docs.ultralytics.com/guides/raspberry-pi/#choose-your-yolo-version-yolov5-or-yolov8
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