Nvidia Jetson Object Detection

Nvidia jetson is a power efficient system on module som with cpu gpu pmic dram and flash storage for edge ai applications that comes in a variety of configuration specifications.

Nvidia jetson object detection. High performance real time object detection on nvidia jetson tx2. Odtk is a single shot object detector with various backbones and detection heads. Nvidia jetson nano is a developer kit which consists of a som system on module and a reference carrier board. This 7 5 watt supercomputer on a module brings true ai computing at the edge.

The detect method of the object returns the location confidence score. The hype of internet of things ai and digitalization have poised the businesses and governmental institutions to embrace this technology as a true problem solving agent. Code your own real time object detection program in python from a live camera feed. Edge computing foresees exponential growth because of developments in sensor technologies network connectivity and artificial intelligence ai.

This article is a project showing how you can create a real time multiple object detection and recognition application in python on the jetson nano developer kit using the raspberry pi camera v2 and deep learning models and libraries that nvidia provides. Here yolo v2 a real time object detection algorithm is tested on nvidia jetson tx2 module an embedded ai computing device. How difficult are object detection and recognition. Jetson tx2 is the fastest most power efficient embedded ai computing device.

This allows performance accuracy trade offs. Nvidia jetson nano future of edge computing. Object detection is the technique of. It is primarily targeted for creating embedded systems that require high processing power for machine learning machine vision and vide.

Nvidia object detection toolkit odtk fast and accurate single stage object detection with end to end gpu optimization. Jetson nano quadruped robot object detection tutorial. The purpose of this blog is to guide users on the creation of a custom object detection model with performance optimization to be used on an nvidia jetson nano. This is a report for a final project.