Welcome to Hailo-10H AI HAT +2 repository

rpicam-apps

The official rpicam-apps camera driver natively supports the AI module, automatically using the NPU to run compatible post-processing tasks.

1. Testing the Camera

To ensure the camera functions correctly, please run the following command:

rpicam-hello -t 10s

This will launch the camera and display a preview window for 10 seconds. Once you've confirmed that everything is installed correctly, you can run some demos.

2. Installation

Note: (No download is required when using the yahboom version image)

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sudo apt update && sudo apt install rpicam-apps

3. Object Detection

This demo shows the bounding boxes around objects detected by the neural network. To disable the viewfinder, use the -n flag. To return plain text output describing the detected objects, add this option. Try the demo on your Raspberry Pi by running the following command: -v 2

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rpicam-hello -t 0 --post-process-file /usr/share/rpi-camera-assets/hailo_yolov6_inference.json

Alternatively, you can try other models with different trade-offs in performance and efficiency.

To run a demo using a Yolov8 model, run the following command:

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rpicam-hello -t 0 --post-process-file /usr/share/rpi-camera-assets/hailo_yolov8_inference.json

To run a demo using a YoloX model, run the following command:

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rpicam-hello -t 0 --post-process-file /usr/share/rpi-camera-assets/hailo_yolox_inference.json

To run the demo using the Yolov5 Person and Face model, run the following command:

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rpicam-hello -t 0 --post-process-file /usr/share/rpi-camera-assets/hailo_yolov5_inference.json

4. Image Segmentation

This demo performs object detection and segments objects by drawing a color mask on the viewfinder image. Try this demo on a Raspberry Pi by running the following command:

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rpicam-hello -t 0 --post-process-file /usr/share/rpi-camera-assets/hailo_yolov5_segmentation.json --framerate 20

5. Attitude estimation

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rpicam-hello -t 0 --post-process-file /usr/share/rpi-camera-assets/hailo_yolov8_pose.json