Edge Insights for Vision

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ID 772621
Date 10/24/2022
Public
Document Table of Contents
Document Table of Contents x
Edge Insights for Vision How it Works Get Started Guide using Linux* Release Notes Documentation Archive
Get Started Guide using Linux* x
Linux* Requirements Install Edge Insights for Vision Introduction to the Edge Software Command Line Interface (CLI) Linux* Troubleshooting Linux* Tutorials
Linux* Tutorials x
Single and Multi-Object Detection with Hardware Acceleration on Linux* Multi-Camera Detection of Social Distancing on Linux*
Single and Multi-Object Detection with Hardware Acceleration on Linux* x
Single and Multi-Object Detection on CPU on Linux* Single and Multi-Object Detection on GPU on Linux* Single and Multi-Object Detection on Intel® Vision Accelerator on Linux*
Edge Insights for Vision
How it Works
Get Started Guide using Linux*
Release Notes
Documentation Archive

Single and Multi-Object Detection with Hardware Acceleration on Linux*

This tutorial uses the sample application called "Object Detection YOLO* V3 Python* Demo." Object Detection YOLO V3 Python Demo uses OpenCV, a component of OpenVINO™, to display a frame with detections that are rendered as bounding boxes and labels, if provided. By default, this sample application displays latency and FPS.

Instructions are provided for three hardware configurations so you can choose the ones that fit your system's configuration:

Parent topic: Linux* Tutorials
Level Two Title