Welcome to the Hailo Raspberry Pi 5 Examples repository. This project showcases various examples demonstrating the capabilities of the Hailo AI processor on a Raspberry Pi 5. These examples will help you get started with AI on embedded devices. Visit the Hailo Official Website and Hailo Community Forum for more information.
- Hailo Raspberry Pi 5 Examples
For installation instructions, see the Hailo Raspberry Pi 5 installation guide.
See the Upgrade or Downgrade Hailo Software section for instructions on how to upgrade the Hailo software.
The Hailo Python API is now available on the Raspberry Pi 5. This API allows you to run inference on the Hailo-8L AI processor using Python. For examples, see our Python code examples. Additional examples can be found in RPi picamera2 code. Visit our HailoRT Python API documentation for more information.
These pipelines are included in this repository. They demonstrate object detection, human pose estimation, and instance segmentation in an easy-to-use format. For installation instructions, see the Basic Pipelines Installation Guide.
Retrained Networks Support
This application includes support for using retrained detection models. For more information, see Using Retrained Models.
CLIP (Contrastive Language-Image Pretraining) predicts the most relevant text prompt on real-time video frames using the Hailo-8L AI processor. See the hailo-CLIP Repository for more information. Click the image below to watch the demo on YouTube.
Frigate is an open-source video surveillance software that runs on a Raspberry Pi. This integration will allow you to use the Hailo-8L AI processor for object detection in real-time video streams.
Raspberry Pi rpicam-apps Hailo post-processing examples. This is Raspberry Pi's official example for AI post-processing using the Hailo AI processor integrated into their CPP camera framework. The documentation on how to use rpicam-apps can be found here. The run command is simplified, and the assets are pre-installed in the system. To run an example from rpicam-apps, run:
rpicam-hello -t 0 --post-process-file /usr/share/rpi-camera-assets/hailo_yolov6_inference.jsonSee more available examples in the /usr/share/rpi-camera-assets directory.
Raspberry Pi picamera2 is the libcamera-based replacement for Picamera, which was a Python interface to the Raspberry Pi's legacy camera stack. Picamera2 also presents an easy-to-use Python API. Run the following command to clone the picamera2 repo and get the example files:
git clone --depth 1 https://github.com/raspberrypi/picamera2The examples will be in ./picamera2/examples/hailo/.
To run an example from picamera2, run:
cd picamera2/examples/hailo/
python3 pose.pyThe Hailo Dataflow Compiler (DFC) is a software tool that enables developers to compile their neural networks to run on the Hailo-8/8L AI processors. The DFC is available for download from the Hailo Developer Zone (Registration required). For examples, tutorials, and retrain instructions, see the Hailo Model Zoo Repo. Additional documentation and tutorials can be found in the Hailo Developer Zone Documentation. For a full end-to-end training and deployment example, see the Retraining Example. The detection basic pipeline example includes support for retrained models. For more information, see Using Retrained Models.
We welcome contributions from the community. You can contribute by:
- Opening a pull request.
- Reporting issues and bugs.
- Suggesting new features or improvements.
- Joining the discussion on the Hailo Community Forum.
This project is licensed under the MIT License. See the LICENSE file for details.
This code example is provided by Hailo solely on an “AS IS” basis and “with all faults.” No responsibility or liability is accepted or shall be imposed upon Hailo regarding the accuracy, merchantability, completeness, or suitability of the code example. Hailo shall not have any liability or responsibility for errors or omissions in, or any business decisions made by you in reliance on this code example or any part of it. If an error occurs when running this example, please open a ticket in the "Issues" tab.