Open Images Dataset

A dataset with approximately 9 million images annotated with image-level labels, object bounding boxes, and visual relationships, useful for diverse image recognition tasks.

About Dataset

The Open Images Dataset is a large-scale collection of approximately nine million images annotated with rich visual labels. Maintained by Google Research, it includes image-level labels, object bounding boxes, object relationships, and segmentation annotations. The dataset covers a wide range of everyday objects, scenes, and interactions, providing diverse and high-quality visual annotations. Open Images emphasizes scale, annotation depth, and coverage of real-world visual concepts, making it one of the most comprehensive open vision datasets available.

Purpose of Dataset

Open Images Is Widely Used For Training And Evaluating Computer Vision Models, Particularly For Object Detection, Image Classification, Segmentation, And Visual Relationship Understanding. Its Rich Annotations Make It Valuable For Both Academic Research And Applied Ai Systems. For Multimodal And Vision–language Models, The Dataset Supports Learning Detailed Object-level Grounding And Visual Semantics, Enabling More Accurate And Robust Visual Understanding.