Learn how to use OpenCV* to count people using edge detection rather than using server farms.
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.
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...
This paper presents a quick hands-on tour of the Inference Engine Python API, using an image classification sample that is included in the OpenVINO™ toolkit 2018 R1.2. This sample uses a public SqueezeNet* model that contains around one thousand object classification labels.
This article provides guidance for transitioning from the NCSDK to the Intel® Distribution of OpenVINO™ toolkit.