OpenVINO™ Tutorial with Segmentation

This tutorial serves as an example for understanding the utilization of the ROS 2 OpenVINO™ node. It outlines the steps for installing and executing the semantic segmentation model using the ROS 2 OpenVINO™ toolkit. This tutorial uses the Intel® RealSense™ camera image as input and performs inference on CPU, GPU devices.

Install OpenVINO™ tutorial packages

sudo apt install ros-humble-segmentation-realsense-tutorial
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Run Demo with Intel® RealSense™ Topic Input

Run one of the following commands to launch the segmentation tutorial with a specific inference engine:

  • GPU inference engine

    ros2 launch segmentation_realsense_tutorial openvino_segmentation.launch.py device:=GPU
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  • CPU inference engine

    ros2 launch segmentation_realsense_tutorial openvino_segmentation.launch.py device:=CPU
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Note

If no device is specified, the GPU is selected by default as inference engine.

Once the tutorial is started, the deeplabv3 model is downloaded, converted into IR files, and the inference process begins, utilizing the input from the Intel® RealSense™ camera.

To exit the application, press Ctrl-c in the terminal where the launch script was executed.

Troubleshooting

For general robot issues, go to: Troubleshooting for Robotics SDK Tutorials .