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TexBiG-v2.0-test
- kaggle.com
Updated Sep 15, 2023+ more versions
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EmailClick to copy linkLink copiedCite(2023). TexBiG-v2.0-test [Dataset]. https://www.kaggle.com/datasets/davidtschirschwitz/texbig-v2-0-testCroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.Dataset updatedSep 15, 2023LicenseAttribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automaticallyDescriptionTexBiG (from the German Text-Bild-Gefüge, meaning Text-Image-Structure) is a document layout analysis dataset for historical documents in the late 19th and early 20th century. The dataset provides instance segmentation (bounding boxes and polygons/masks) annotations for 19 different classes. Annotations are manually annotated by experts, with each image annotated five times. This annotations are then aggregated to approximate a ground truth.
This version of the dataset contains the test data, which are available on EvalAI for public evaluation.
TexBiG Dataset for Analysing Complex Document Layouts in the Digital...
- zenodo.org
bin, pdf, zipUpdated Sep 27, 2023ShareFacebookTwitterEmailClick to copy linkLink copiedCiteDavid Tschirschwitz; David Tschirschwitz; Franziska Klemstein; Franziska Klemstein; Benno Stein; Benno Stein; Volker Rodehorst; Volker Rodehorst (2023). TexBiG Dataset for Analysing Complex Document Layouts in the Digital Humanities [Dataset]. http://doi.org/10.5281/zenodo.6885144zip, bin, pdfAvailable download formatsUnique identifierhttps://doi.org/10.5281/zenodo.6885144Dataset updatedSep 27, 2023AuthorsDavid Tschirschwitz; David Tschirschwitz; Franziska Klemstein; Franziska Klemstein; Benno Stein; Benno Stein; Volker Rodehorst; Volker RodehorstLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionThis is the dataset for the paper "A Dataset for Analysing Complex Document Layouts in the Digital Humanities and its Evaluation with Krippendorff ’s Alpha". TexBiG (from the German Text-Bild-Gefüge, meaning Text-Image-Structure) is a document layout analysis dataset for historical documents in the late 19th and early 20th century. The dataset provides instance segmentation (bounding boxes and polygons/masks) annotations for 19 different classes with more then 52.000 instances.
Annotations are manually annotated by experts and evaluated with Krippendorff's Alpha, for each document image are least two different annotators have labeled the document. Further details can be found in the Paper.TexBiG Dataset for Analysing Complex Document Layouts in the Digital...
- zenodo.org
- explore.openaire.eu
zipUpdated Sep 27, 2023ShareFacebookTwitterEmailClick to copy linkLink copiedCiteDavid Tschirschwitz; David Tschirschwitz; Franziska Klemstein; Franziska Klemstein; Benno Stein; Benno Stein; Volker Rodehorst; Volker Rodehorst (2023). TexBiG Dataset for Analysing Complex Document Layouts in the Digital Humanities [Dataset]. http://doi.org/10.5281/zenodo.8347059zipAvailable download formatsUnique identifierhttps://doi.org/10.5281/zenodo.8347059Dataset updatedSep 27, 2023AuthorsDavid Tschirschwitz; David Tschirschwitz; Franziska Klemstein; Franziska Klemstein; Benno Stein; Benno Stein; Volker Rodehorst; Volker RodehorstLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionThis is the dataset for the paper "A Dataset for Analysing Complex Document Layouts in the Digital Humanities and its Evaluation with Krippendorff ’s Alpha" in its second version, containing an update of the test images (without annotations) from the paper "Drawing the Same Bounding Box Twice? Coping Noisy Annotations in Object Detection with Repeated Labels". Organization of the dataset is also updated to make it easier to use.
TexBiG (from the German Text-Bild-Gefüge, meaning Text-Image-Structure) is a document layout analysis dataset for historical documents in the late 19th and early 20th century. The dataset provides instance segmentation (bounding boxes and polygons/masks) annotations for 19 different classes with more then 52.000 instances. The added test images can be used to make submission on the leaderboard on EvalAI.
The annotation guideline can be found in the first of the dataset.
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FacebookTwitterEmailAttribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
TexBiG (from the German Text-Bild-Gefüge, meaning Text-Image-Structure) is a document layout analysis dataset for historical documents in the late 19th and early 20th century. The dataset provides instance segmentation (bounding boxes and polygons/masks) annotations for 19 different classes. Annotations are manually annotated by experts, with each image annotated five times. This annotations are then aggregated to approximate a ground truth.
This version of the dataset contains the test data, which are available on EvalAI for public evaluation.