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Hailo Raspberry Pi 5 Examples

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. Check out Hailo Official Website and Hailo Community Forum for more information.

Table of Contents

Raspberry Pi 5 with Hailo M.2

Hailo Packages Installation

For installation instructions, see Hailo Raspberry Pi 5 installation guide.

Available Examples and Resources

Hailo Dataflow Compiler (DFC) is now available

The 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 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.

Hailo Examples

Basic Pipelines (Python)

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 Basic Pipelines Installation Guide.

NEW: Retrained networks support

This application includes support for using retrained detection models. For more information, see Using Retrained Models.

Detection Example

Detection Example

Pose Estimation Example

Pose Estimation Example

Instance Segmentation Example

Instance Segmentation Example

CLIP Application - Coming Soon

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text prompt on real-time video frames using the Hailo-8L AI processor.

Raspberry Pi Official Examples

rpicam-apps

Raspberry Pi rpicam-apps Hailo post process 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 the rpicam-apps can be found here. To run an example from the rpicam-apps, follow the instructions below: Clone the rpicam-apps repository to get the JSON configuration files

  git clone --depth 1 https://github.com/raspberrypi/rpicam-apps.git

Change directory to the assets folder and run the example

  cd rpicam-apps/assets/
  # Run the example
  rpicam-hello -t 0 --post-process-file hailo_yolov6_inference.json --lores-width 640 --lores-height 640

picamera2 - Coming Soon

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.

Contributing

We welcome contributions from the community. You can contribute by:

  1. Opening a pull request.
  2. Reporting issues and bugs.
  3. Suggesting new features or improvements.
  4. Joining the discussion on the Hailo Community Forum.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Disclaimer

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.