You can use GPU Coder™ in tandem with the Deep Learning Toolbox™ to generate code and deploy deep learning networks on embedded platforms that use NVIDIA® Jetson and Drive platforms. The pretrained networks and examples such as object detection, image classification, and driver assistance applications make it easy to use GPU Coder for deep learning, even without expert knowledge on neural networks, deep learning, or advanced computer vision algorithms.
We start with a published example in MATLAB that explains how to train a YOLO v2 object detector and, using GPU Coder™, we generate optimized CUDA code and using the hardware support package for NVIDIA® GPUs, we deploy the generated code to the Jetson Xavier board as a standalone application.
The download contains the additional scripts and the functions that you could use to generate code.
Please refer to the following documentation link for the example in MATLAB and all the necessary files:
Object Detection Using YOLO v2 Deep Learning: https://www.mathworks.com/help/vision/ug/train-an-object-detector-using-you-only-look-once.html
MathWorks GPU Coder Community Profile (2020). Real-Time Object Detection with YOLO v2 Using GPU Coder (https://www.mathworks.com/matlabcentral/fileexchange/71259-real-time-object-detection-with-yolo-v2-using-gpu-coder), MATLAB Central File Exchange. Retrieved .