The HaGRID dataset contains 1.08 million images covering 33 gesture classes plus a no-gesture class, with 65,977 unique subjects. It supports both image classification and object detection tasks for hand gesture recognition systems in domains like video conferencing, home automation, and automotive. The dataset includes pre-defined train/validation/test splits by user ID and was collected with varied lighting conditions.