We present a streamlined pipeline that generates a YOLO object detection application using MATLAB software and NVIDIA® hardware. The application utilizes MATLAB GPU Coder and NVIDIA® TensorRT™ to accelerate inferencing on NVIDIA processors, specifically the latest Jetson Orin™ embedded processor. We evaluated the object detector on the open U.S. Army Automated Target Recognition (ATR) Development Image Dataset (ADID) for multi-class vehicle detection and classification. Overall, this workflow decreases development time over traditional approaches and provides a quick route to low-code deployment on the latest NVIDIA Jetson Orin. This work offers value to researchers and practitioners in many application areas aiming to harness the power of NVIDIA processors for rapid, efficient object detection solutions.
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