Images from sources on this page are available for use on the open web. You are free to use these images in multimedia projects, websites, blogs, portfolios, etc, that are open and available to the public. When you use these images, you do not need to restrict access to your class or academic environment.

The dataset is a product of a collaboration between Google, CMU and Cornell universities, and there are a number of research papers built on top of the Open Images dataset in the works. It is our hope that datasets like Open Images and the recently released YouTube-8M will be useful tools for the machine learning community.

Much of this progress can be attributed to publicly available image datasets, such as ImageNet and COCO for supervised learning, and YFCC100M for unsupervised learning. Today, we introduce Open Images, a dataset consisting of ~9 million URLs to images that have been annotated with labels spanning over 6000 categories.

The image dataset for new algorithms is organised according to the WordNet hierarchy, in which each node of the hierarchy is depicted by hundreds and thousands of images. Downloading datasets isn’t instant though, you’ll have to register on the site, hover over the ‘download’ menu dropdown, then select ‘original images’.