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  • Writer's pictureMichael Gruner

NVIDIA DeepStream Reference

Automatic Parking Lot Vehicle Registration


Implementing a DeepStream pipeline to detect objects of interest is only one of the many components that compose an AI powered system. Using these predictions to perform business decisions is yet another challenge. RidgeRun is creating a set of Python reference designs to be used as robust, modular and extensible starting points for applications using deep learning in some form.

Our first reference design is the Automatic Parking Lot Vehicle Registration which implements a system capable of identifying the time, date and location of some predefined events. More specifically:

  • License plate enters the premise

  • License plate parks on/leaves a parking stall

  • License plate leaves the premise

The reference design is composed by several components:

  • RTSP camera capture

  • DeepStream based license plate detection

  • Event logging to a web dashboard

  • Snapshot taking of every event

  • Comprehensive design and customization documentation

Three cameras capturing different sections of a parking lot. Cars in the parking lot have been successfully predicted. A web dashboard displays past occurred events.

Give your application a head start and reduce your time-to-market. Learn more in our developers wiki.

Make sure to contact us if you'd like to explore RidgeRun's DeepStream Reference Designs.

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