19th Century United States Newspaper Advert images with 'illustrated' or 'non illustrated' labels

The Dataset contains images derived from the Newspaper Navigator (news-navigator.labs.loc.gov/), a dataset of images drawn from the Library of Congress Chronicling America collection (chroniclingamerica.loc.gov/). [The Newspaper Navigator dataset] consists of extracted visual content for 16,358,041 historic newspaper pages in <em>Chronicling America</em>. The visual content was identified using an object detection model trained on annotations of World War 1-era Chronicling America pages, including annotations made by volunteers as part of the Beyond Words crowdsourcing project. source: https://news-navigator.labs.loc.gov/ One of these categories is 'advertisements. This dataset contains a sample of these images with additional labels indicating if the advert is 'illustrated' or 'not illustrated'. The data is organised as follows: The images themselves can be found in `images.zip` `newspaper-navigator-sample-metadata.csv` contains metadata about each image drawn from the Newspaper Navigator Dataset. `ads.csv` contains the labels for the images as a CSV file `sample.csv` contains additional metadata about the images (based on the newspapers those images came from). This dataset was created for use in an under-review Programming Historian tutorial (http://programminghistorian.github.io/ph-submissions/lessons/computer-vision-deep-learning-pt1) The primary aim of the data was to provide a realistic example dataset for teaching computer vision for working with digitised heritage material. The data is shared here since it may be useful for others. <strong>This data documentation is a work in progress and will be updated when the Programming Historian tutorial is released publicly. </strong> The metadata CSV file contains the following columns: - filepath<br> - pub_date<br> - page_seq_num<br> - edition_seq_num<br> - batch<br> - lccn<br> - box<br> - score<br> - ocr<br> - place_of_publication<br> - geographic_coverage<br> - name<br> - publisher<br> - url<br> - page_url<br> - month<br> - year<br> - iiif_url本数据集包含源自《报纸导航器（Newspaper Navigator）》（news-navigator.labs.loc.gov/）的图像，该数据集提取自美国国会图书馆《编年史美国（Chronicling America）》馆藏（chroniclingamerica.loc.gov/）。<em>《报纸导航器数据集（Newspaper Navigator Dataset）》</em>包含从16,358,041页<em>Chronicling America</em>历史报纸页面中提取的视觉内容。上述视觉内容通过在第一次世界大战时期<em>Chronicling America</em>页面的标注集上训练的目标检测模型（object detection model）识别得到，其中标注工作由志愿者作为"超越文字（Beyond Words）"众包项目的一部分完成。来源：https://news-navigator.labs.loc.gov/。其中一个类别为"广告（advertisements）"。本数据集为该数据集的样本子集，并额外添加了标注，用于指示广告属于"带插图（illustrated）"还是"无插图（not illustrated）"。数据组织形式如下：图像文件均存放于`images.zip`压缩包中；`newspaper-navigator-sample-metadata.csv`包含源自《报纸导航器数据集》的每张图像的元数据；`ads.csv`以CSV格式存储了图像的标注标签；`sample.csv`包含关于图像的额外元数据（基于图像来源报纸的相关信息）。本数据集为一篇正在审稿中的《编程史学家（Programming Historian）》教程（http://programminghistorian.github.io/ph-submissions/lessons/computer-vision-deep-learning-pt1）所创建，其核心目标是提供一个贴合实际的示例数据集，用于教授如何针对数字化遗产材料开展计算机视觉相关工作。本数据集在此分享，以期对其他研究者有所助益。<strong>本数据文档仍在完善中，待《编程史学家》教程正式公开上线后将进行更新。</strong> 元数据CSV文件包含以下列：<br>- filepath（文件路径）<br>- pub_date（出版日期）<br>- page_seq_num（页面序号）<br>- edition_seq_num（版次序号）<br>- batch（批次）<br>- lccn（美国国会图书馆控制号，Library of Congress Control Number）<br>- box（盒号）<br>- score（置信度得分）<br>- ocr（光学字符识别结果，Optical Character Recognition）<br>- place_of_publication（出版地点）<br>- geographic_coverage（地理覆盖范围）<br>- name（报纸名称）<br>- publisher（出版方）<br>- url（资源链接）<br>- page_url（页面链接）<br>- month（月份）<br>- year（年份）<br>- iiif_url（国际图像互操作框架链接，International Image Interoperability Framework URL）