This application performs real-time object detection using a YOLOv6 Nano model and stereo depth estimation (if the device has stereo cameras). It streams raw video, H.264/MJPEG encoded video, object detection results, and a colorized depth map to a remote visualizer for monitoring and analysis.
Running this example requires a Luxonis device connected to your computer. Refer to the documentation to setup your device if you haven't done it already.
You can run the example fully on device (STANDALONE mode) or using your computer as host (PERIPHERAL mode).
Here is a list of all available parameters:
-d DEVICE, --device DEVICE
Optional name, DeviceID or IP of the camera to connect to. (default: None)
You need to first prepare a Python 3.10 environment with the following packages installed:
You can simply install them by running:
pip install -r requirements.txtRunning in peripheral mode requires a host computer and there will be communication between device and host which could affect the overall speed of the app. Below are some examples of how to run the example.
python3 main.pyThis will run the example with default arguments.
Running the example in the standalone mode, app runs entirely on the device.
To run the example in this mode, first install the oakctl tool using the installation instructions here.
The app can then be run with:
oakctl connect <DEVICE_IP>
oakctl app run .This will run the example with default argument values. If you want to change these values you need to edit the oakapp.toml file (refer here for more information about this configuration file).
