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Whether you’re integrating an object detector into an existing application or deploying it to hardware, you have a few options when determining how to package the detector. This step-by-step guide teaches you how to turn your model into a functional component of your project, first showing how to create a static library using MATLAB Coder™ and then taking you through the steps of creating an ROS 2 node. These deployment options allow you to integrate your model seamlessly into various applications, from standalone software to robotic systems. Check out the other videos in the Deep Learning for 3D Object Detection series: • Deep Learning for 3D Object Detection Related Resources: Access the materials for this video: https://bit.ly/3D-object-detection R2025b Supported and Compatible Compilers - Windows: https://bit.ly/4pHc49E MATLAB Coder Documentation: https://bit.ly/3Keif4B Prerequisites for Deep Learning with MATLAB Coder: https://bit.ly/3Iyjye3 Installing Prerequisite Products: https://bit.ly/3KzJV3W Chapters: 0:00 Introduction 0:29 Prerequisites for code generation 3:42 What is a static library 4:31 Code generation workflow 6:19 Set up MATLAB Coder with the coder app 8:03 Explore coder settings 12:10 Check for issues and generate a static library 14:45 Explore the generated code 18:10 ROS 2 nodes and coder configuration 20:56 Creating a ROS 2 node in MATLAB 23:16 Generate a deploy a ROS 2 node to a Jetson device 24:48 Conclusion -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2025 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.