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Dataset Card for Early Printed Books Font Detection Dataset
Dataset Summary
This dataset is composed of photos of various resolution of 35'623 pages of printed books dating from the 15th to the 18th century. Each page has been attributed by experts from one to five labels corresponding to the font groups used in the text, with two extra-classes for non-textual content and fonts not present in the following list: Antiqua, Bastaπrda, Fraktur, Gotico Antiqua, Greek, Hebrew, Italic, Rotunda, Schwabacher, and Textura.
[More Information Needed]
Supported Tasks and Leaderboards
The primary use case for this datasets is
multi-label-image-classification: This dataset can be used to train a model for multi label image classification where each image can have one, or more labels.image-classification: This dataset could also be adapted to only predict a single label for each image
Languages
The dataset includes books from a range of libraries (see below for further details). The paper doesn't provide a detailed overview of language breakdown. However, the books are from the 15th-18th century and appear to be dominated by European languages from that time period. The dataset also includes Hebrew.
[More Information Needed]
Dataset Structure
This dataset has a single configuration.
Data Instances
An example instance from this dataset:
{'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=3072x3840 at 0x7F6AC192D850>,
'labels': [5]}
Data Fields
This dataset contains two fields:
image: the image of the book pagelabels: one or more labels for the font used in the book page depicted in theimage
Data Splits
The dataset is broken into a train and test split with the following breakdown of number of examples:
- train: 24,866
- test: 10,757
Dataset Creation
Curation Rationale
The dataset was created to help train and evaluate automatic methods for font detection. The paper describing the paper also states that:
data was cherry-picked, thus it is not statistically representative of what can be found in libraries. For example, as we had a small amount of Textura at the start, we specifically looked for more pages containing this font group, so we can expect that less than 3.6 % of randomly selected pages from libraries would contain Textura.
Source Data
Initial Data Collection and Normalization
The images in this dataset are from books held by the British Library (London), Bayerische Staatsbibliothek München, Staatsbibliothek zu Berlin, Universitätsbibliothek Erlangen, Universitätsbibliothek Heidelberg, Staats- und Universitäatsbibliothek Göttingen, Stadt- und Universitätsbibliothek Köln, Württembergische Landesbibliothek Stuttgart and Herzog August Bibliothek Wolfenbüttel.
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Who are the source language producers?
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Annotations
Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Considerations for Using the Data
Social Impact of Dataset
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Discussion of Biases
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Other Known Limitations
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Additional Information
Dataset Curators
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Licensing Information
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Citation Information
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Contributions
Thanks to @github-username for adding this dataset.
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