Booknis

The Booknis dataset is a collection of manually annotated images featuring medieval singing representations for segmentation and object detection.
These images are derived from manuscripts that date back to the period between the 12th and 15th centuries and consist of various genres, including liturgical, secular, musical, scientific, and historical works.
The dataset includes five classes, namely books, altars, lecterns, sheets, and phylacteries, which serve as indicators of potential musical representation.
We have meticulously annotated 341 images and 1513 annotations, which musicology experts have verified.
The primary objective of Booknis is to advance research on transfer learning by providing a more challenging benchmark for few-shot object detection.

Booknis数据集是一套经手动标注的图像集合，专为中世纪歌唱表现场景的分割与目标检测任务构建。这些图像源自12至15世纪的手稿，涵盖礼拜仪式、世俗、音乐、科学及历史等多种题材类型。该数据集包含五个类别，分别为书籍、祭坛、读经台、书页与经符牌（phylacteries），上述类别均可作为潜在音乐表现形式的识别标识。我们已完成341张图像的精细标注，总计1513个标注条目，且经音乐学专家核验确认。Booknis数据集的核心目标是通过为少样本（few-shot）目标检测提供更具挑战性的基准测试集，推动迁移学习相关研究的发展。