AWS launches Amazon Rekognition Custom Labels to enable customers to find objects and scenes unique to their business in images
Today, Amazon Web Services (AWS) launched Amazon Rekognition Custom Labels, a new feature of Amazon Rekognition that enables customers to build their own machine learning (ML) based image analysis capabilities to detect unique objects and scenes, relevant to their business need. For example, customers using Amazon Rekognition to detect machine parts from images can now train a ML model with a small set of labeled images to detect “turbochargers” and “torque converters” without needing any ML expertise. Instead of having to train a model from scratch, which requires specialized machine learning expertise and millions of high-quality labeled images, customers can now use Amazon Rekognition Custom Labels to achieve state-of-the-art performance for their unique image analysis needs.
NFL Media, part of the National Football League, manages an exponentially-growing library of videos and images that is difficult to search for relevant content such team logos, pylons, or foam fingers with traditional methods. Amazon Rekognition Custom Labels makes that easier, says Brad Boim, NFL Senior Director of Post Production and Asset Management. “By using the new feature in Amazon Rekognition, Custom Labels, we are able to automatically generate metadata tags tailored to specific use cases for our business and provide searchable facets for our content creation teams. This significantly improves the speed in which we can search for content and, more importantly, it enables us to automatically tag elements that required manual efforts before. These tools allow our production teams to leverage this data directly and provides enhanced products to our customers across all of our media platforms.”
Amazon Rekognition Custom Labels is now generally available in US East (N.Virginia), US East (Ohio), US West (Oregon), and EU (Ireland) regions. To learn more, visit this page.