https://www.raspberrypi.com/products/raspberry-pi-5/
- Arm Cortex-A Processor Comparison Table
- 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 (2GB, 4GB, 8GB, and 16GB)
- 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
https://datasheets.raspberrypi.com/rpi5/raspberry-pi-5-product-brief.pdf
- Raspberry Pi AI Kit
- https://www.raspberrypi.com/products/ai-kit/
- 13 TOPS Hailo-8L accelerator at USD 70
- Raspberry Pi AI HAT+
- https://www.raspberrypi.com/news/raspberry-pi-ai-hat/
- 26 TOPS Hailo-8 accelerator at USD 110
- Raspberry Pi Al HAT+ 2 [SeeedStudio]
- Hailo-10H AI Accelerator 40 TOPS at USD 180
https://datasheets.raspberrypi.com/hat/hat-plus-specification.pdf
- A guide to designing Hardware-Attached-on-Top of a Raspberry Pi
- HAT+ boards should use 'HAT+' in their name. For example, "Raspberry Pi M.2 HAT+ M Key"
- Unlike the AI Kit, which utilises an M.2 connector, the Hailo accelerator chip is directly integrated onto the main PCB.
Tech Spec: https://www.raspberrypi.com/products/raspberry-pi-5/
- 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 (2GB, 4GB, and 8GB)
- 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, 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 OS (previously called Raspbian)
- Raspberry Pi Connect provides to access your Raspberry Pi from anywhere
The Raspberry Pi 5 AI Kit bundles the Raspberry Pi M.2 HAT+ with a Hailo AI acceleration module. The kit contains the following:
- Hailo AI module containing a Neural Processing Unit (NPU)
- Raspberry Pi M.2 HAT+, to connect the AI module to your Raspberry Pi 5
- Thermal pad pre-fitted between the module and the M.2 HAT+
- Mounting hardware kit
- 16mm stacking GPIO header
Run the following command from a terminal window:
$ sudo apt install hailo-all
$ sudo apt remove hailo-all
This installs the following dependencies:
- Hailo kernel device driver and firmware
- HailoRT middleware software
- Hailo Tappas core post-processing libraries
- rpicam-apps: Hailo post-processing software demo
$ hailortcli scan
$ hailortcli fw-control identify
The log message will be:
Executing on device: 0000:04:00.0
Identifying board
Control Protocol Version: 2
Firmware Version: 4.20.0 (release,app,extended context switch buffer)
Logger Version: 0
Board Name: Hailo-8
Device Architecture: HAILO8L
Serial Number: HLDDLBB243900626
Part Number: HM21LB1C2LAE
Product Name: HAILO-8L AI ACC M.2 B+M KEY MODULE EXT TMP
$ lspci
0000:00:00.0 PCI bridge: Broadcom Inc. and subsidiaries BCM2712 PCIe Bridge (rev 21)
0000:01:00.0 Co-processor: Hailo Technologies Ltd. Hailo-8 AI Processor (rev 01)
0001:00:00.0 PCI bridge: Broadcom Inc. and subsidiaries BCM2712 PCIe Bridge (rev 21)
0001:01:00.0 Ethernet controller: Raspberry Pi Ltd RP1 PCIe 2.0 South Bridge
https://github.com/hailo-ai/hailo-rpi5-examples
- Clone the repository and navigate to the repository directory:
- Run the following script for quick installation
$ git clone https://github.com/hailo-ai/hailo-rpi5-examples.git
$ cd hailo-rpi5-examples
$ ./install.sh
This example demonstrates object detection using the YOLOv8s model for Hailo-8L (13 TOPS) and the YOLOv8m model for Hailo-8 (26 TOPS) by default. It also supports all models compiled with HailoRT NMS post process. Hailo's Non-Maximum Suppression (NMS) layer is integrated into the HEF file, allowing any detection network compiled with NMS to function with the same codebase.
- Opening a new terminal session and sourced the environment setup script
- Run the detection example using Python script
- To close the application, press Ctrl+C.
$ source setup_env.sh
$ python basic_pipelines/detection.py
$ python basic_pipelines/get_usb_camera.py
$ python basic_pipelines/detection.py --input /dev/video0
$ python basic_pipelines/detection.py --help
This example demonstrates human pose estimation using the yolov8s_pose model for Hailo-8 Lite (H8l) and the yolov8m_pose model for Hailo-8 (H8)
- Opening a new terminal session andsourced the environment setup script
- Run the example using Python script
- To close the application, press Ctrl+C
- For additional options, execute command with --help option
$ source setup_env.sh
$ python basic_pipelines/pose_estimation.py
$ python basic_pipelines/get_usb_camera.py
$ python basic_pipelines/pose_estimation.py --input /dev/video0
$ python basic_pipelines/pose_estimation.py --help
This example demonstrates instance segmentation using the yolov5n_seg model for Hailo-8 Lite (H8l) and the yolov5m_seg model for Hailo-8 (H8).
- Opening a new terminal session andsourced the environment setup script
- Run the example using Python script
- To close the application, press Ctrl+C
- For additional options, execute command with --help option
$ source setup_env.sh
$ python basic_pipelines/instance_segmentation.py
$ python basic_pipelines/get_usb_camera.py
$ python basic_pipelines/instance_segmentation.py --input /dev/video0
$ python basic_pipelines/instance_segmentation.py --help
- Introduction to AI
- Set up your Raspberry Pi and AI Kit
- Computer vision projects and practice
- LLM projects and practice
- Custom model development and deployment
- Raspberry Pi and AIoT
- Raspberry Pi hardware - Introduction
- Raspberry Pi 5 uses PCIe hat/dual hat
- Raspberry Pi - AI Kit and AI HAT+ software
- Install Hailo Software & Verify Installation
- Hailo’s Software Downloads and Documentation
- HailoRT v4.19.0 - Installing HailoRT on Ubuntu
- HailoRT v4.20.0 documentation
- Hailo TAPPAS - Optimized Execution of Video-Processing Pipelines:
- Hailo Raspberry Pi5 Examples
- Hailo RPi5 Basic Pipelines
- RPI5 + Hailo8 - CLIP Application
- Pose-Based Light Control with Node-Red and Raspberry Pi with AIkit
- Benchmark of Multistream Inference on Raspberrypi 5 with Hailo8
- YOLOv8 - Ultralytics
- Testing Raspberry Pi's AI Kit - 13 TOPS for $70 (2024.07)