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Webinar: How to Run Real Time Detection on 8 Live Streams Using 1 NVIDIA Jetson Xavier NX

  • Engineering Team
  • 2 min read

AI-based video analytics applications are powered by various computer vision models that need to process video footage or live streams in real time and on edge devices.

In this webinar, you’ll learn how to process in real time 8 video streams while using only 1 NVIDIA Jetson Xavier NX device.

Join Avi Lumelsky, Software Architect, and Nave Assaf, Deep Learning Engineer, and discover:

  • The end-to-end pipeline that enables 8 live video streams to run on a NVIDIA Jetson in real time
  • Engineering tips on getting the most out of your edge hardware
  • A NAS-generated object detection model, that outperforms SOTA models and enables you to achieve better hardware utilization

Do you want to get similar results for your use case? Book a demo of our Deep Learning Development Platform or chat with one of our deep learning experts.

Book a Demo

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					from transformers import AutoFeatureExtractor, AutoModelForImageClassification

extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")

model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-50")