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Article

Building OpenCV* 3.0-based embedded application using Intel® System Studio 2015

We describe how to use Intel® System Studio 2015 to build the OpenCV* 3.0-based embedded application on Intel platforms. In this paper, we have considered a sample code that is part of OpenCV, how to use different components of Intel® System Studio to build OpenCV sample code.
Автор: Последнее обновление: 13.12.2018 - 14:10
Article

Enabling Intel® IPP on OpenCV* (Windows* and Ubuntu*)

Instructions to set up the environment of IPP on OpenCV on Windows* or Linux* Ubuntu*.
Автор: JON J K. (Intel) Последнее обновление: 31.07.2019 - 14:30
Article

Code Sample: Use LibRealSense and OpenCV* to stream RGB and Depth Data

You can use LibRealSense and OpenCV* to stream RGB and depth data from your connected Intel® RealSense™ camera. This tutorial and code sample shows how to do this, based on the Ubuntu* operating system. In the end you will have a nice starting point where you use this code base to build upon to create your own LibRealSense / OpenCV applications.
Автор: Rick Blacker (Intel) Последнее обновление: 18.01.2018 - 16:13
Article

Counting People: Use OpenCV* for Edge Detection

Learn how to use OpenCV* to count people using edge detection rather than using server farms.
Автор: Foster, Whitney (Intel) Последнее обновление: 31.05.2019 - 09:24
Документация
Article

Python* Code Samples for Video Analytics with OpenCV

In support of computer vision development efforts, we've created a GitHub* repository of twelve computer vision code samples. These code samples are a good starting point for developers who wish to develop more robust computer vision and analytic solutions. We use the Retail, Digital Signage market in these examples but the technology can be used in a variety of different markets.
Автор: Kevin R. (Intel) Последнее обновление: 10.07.2018 - 08:00
Article

An update to the integration of Intel® Media SDK and FFmpeg

Introduction
Автор: Liu, Mark (Intel) Последнее обновление: 03.07.2019 - 20:00
Документация

Inference of Caffe* and TensorFlow* Trained Models with Intel’s Deep Learning Deployment Toolkit Beta 2017R3

Installing Deployment Toolkit
Последнее обновление: 22.01.2019 - 10:29
Документация
Article

Edge Data Processing POC with the UP Squared* Board

With the amount of continuously generated data on the rise, the cost to upload and store that data in the cloud is increasing. Data is being gathered faster than it is stored and immediate action is often required. Sending all the data to the cloud can result in latency and presents risks when internet connectivity is intermittent. Edge computing involves processing data locally for immediate...
Автор: Foster, Whitney (Intel) Последнее обновление: 29.10.2018 - 13:01