A dataset of Manchu ancient book words for OCR

This dataset consists of 24,280 high-resolution word images extracted from Manchu ancient books dating from 1733 to 1867, collected within the present-day territory of China. The images were sourced from the Series of Rare Ancient Books in Manchu and Chinese curated by the National Library of China. Each of the 2,428 unique Manchu words in the dataset is represented by exactly 10 distinct image samples, resulting in a balanced and well-structured dataset suitable for training and evaluating deep learning models in the task of Manchu OCR (optical character recognition).This dataset was constructed using a semi-automated workflow to address the challenges posed by manual segmentation of historical scripts—such as high annotation costs and time-consuming processing—and to preserve the visual details of each page. The image acquisition process involved high-precision scanning at 600 dpi. Word regions were first identified using computer vision algorithms, followed by manual verification and correction to ensure the accuracy and completeness of the extracted samples.All images are stored in standard .jpg format with consistent resolution and naming conventions. The dataset is divided into structured folders by word category, and accompanying metadata files provide annotations, including word labels, file paths, and page source references. The released version has no missing data entries, and the dataset has been quality-checked to exclude samples with severe degradation, such as illegible characters, torn pages, or significant shadowing.To our knowledge, this is the largest publicly available Manchu word image dataset to date. It offers a valuable resource for researchers in historical document analysis, Manchu linguistics, and machine learning-based OCR. The dataset can be used for model training and evaluation, benchmarking segmentation algorithms, and exploring multimodal representations of Manchu script.