Google has published the fourth version of its Open Images dataset, the largest publicly accessible dataset of images with object location annotations, to provide researchers with a resource to create better computer vision models. The dataset consists of a training set of over nine million labeled images and annotations describing 600 classes of objects. Open Images also includes a validation set of over 40,000 images and a test set of over 125,000 with human verified labels to enable developers to evaluate their models.
Accelerating Computer Vision Research
Michael McLaughlin is a research assistant at the Center for Data Innovation. He previously worked at Oracle and held internships at USA TODAY and in local government. Prior to joining the Center for Data Innovation, Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He is currently pursuing his Master’s in Communication at Stanford University, specializing in Data Journalism.
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