ShelfAura: A Dataset for Book Spine Detection and Recognition

This dataset, ShelfAura, is designed for the tasks of book spine detection, segmentation, and optical character recognition (OCR) in library and bookstore environments. It consists of 111 high-resolution images of bookshelves containing approximately 1,754 individual book spines. Key features: 111 raw shelf images. 1,754 manually annotated and cropped book spine images. Annotations provided for text recognition on spines. Optimized for training models like YOLO, Florence-2, Qwen and TrOCR. This dataset supports research in automated inventory management and digital library organization.