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，该工具是针对美国国会图书馆《长期美国报纸档案（Chronicling America，chroniclingamerica.loc.gov/）》馆藏制作的图像数据集。报纸导航器数据集（Newspaper Navigator Dataset）包含了《长期美国报纸档案（Chronicling America）》中16358041份历史报纸页面的提取视觉内容。这些视觉内容通过基于第一次世界大战时期《长期美国报纸档案》页面标注训练得到的目标检测模型识别，其中标注工作由志愿者参与完成，属于“超越文字（Beyond Words）”众包项目的一部分。数据来源：https://news-navigator.labs.loc.gov/ 该数据集的分类之一为“广告（advertisements）”。本数据集抽取了其中一部分图像，并为每张图像附加标签，标注其广告属于“带插图（illustrated）”或“无插图（not illustrated）”类别。 本数据集的文件结构如下： 图像文件均可在`images.zip`中获取；`newspaper-navigator-sample-metadata.csv`包含取自报纸导航器数据集的每张图像的元数据；`ads.csv`以CSV格式存储图像的分类标签；`sample.csv`则包含关于图像来源报纸的额外元数据。 本数据集专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）而制作。该数据集的核心目标是提供一个贴合实际的示例数据集，用于教授计算机视觉技术在数字化遗产材料处理中的应用。本次公开分享该数据集，是因为其可能对其他研究者有所助益。 **本数据文档仍在完善中，待《编程史学家》教程正式公开后将进行更新。** 该元数据CSV文件包含以下字段： - filepath：文件路径 - pub_date：出版日期 - page_seq_num：页面序列编号 - edition_seq_num：版次序列编号 - batch：数据批次 - lccn：国会图书馆控制号（Library of Congress Control Number） - box：档案盒编号 - score：目标检测模型置信度得分 - ocr：光学字符识别（Optical Character Recognition）结果 - place_of_publication：出版地 - geographic_coverage：地理覆盖范围 - name：报纸名称 - publisher：出版方 - url：资源链接 - page_url：报纸页面链接 - month：出版月份 - year：出版年份 - iiif_url：国际图像互操作框架（International Image Interoperability Framework）链接