Deploy YOLOv2 to an NVIDIA Jetson
From the series: Perception
In this video, Connell D’Souza joins Neha Goel to demonstrate how to deploy a deep neural network to an NVIDIA® embedded GPU using GPU Coder™ and the GPU Coder support package for NVIDIA GPUs. The example discussed in this video is deploying a multiclass YOLOv2 neural network to an NVIDIA Jetson® TX1.
Connell first introduces the different MathWorks and third-party prerequisite libraries needed to generate and deploy CUDA code to an NVIDIA GPU and demonstrates how to verify the setup using the coder.checkGpuInstall app.
Next, Connell will discuss preparing MATLAB code for GPU code generation. He demonstrate how to generate and deploy an executable to an NVIDIA Jetson TX1 to sample video frames from a camera connected to the Jetson and detect objects of interest in the video frames.
You can also select a web site from the following list:
How to Get Best Site Performance
Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.