This repository provides a Jupyter notebook that uses a YOLOv8 model to extract figures from a book given the url of its iiif manifest.
The model has been trained on the following fives book from the ABO corpus:
-[](http://data.onb.ac.at/ABO/%2BZ97792402)
-[](http://data.onb.ac.at/ABO/%2BZ155502807)
-[](http://data.onb.ac.at/ABO/%2BZ156318706)
-[](http://data.onb.ac.at/ABO/%2BZ164403901)
-[](http://data.onb.ac.at/ABO/%Z259182702)
- http://data.onb.ac.at/ABO/%2BZ97792402
- http://data.onb.ac.at/ABO/%2BZ155502807
- http://data.onb.ac.at/ABO/%2BZ156318706
- http://data.onb.ac.at/ABO/%2BZ164403901
- http://data.onb.ac.at/ABO/%Z259182702
From these approximately 1700 book pages 250 contain figures that have been annotated with bounding boxes with the image annotation webservice [CVAT](https://www.cvat.ai/). Training has been done locally with the nano version of YOLOv8. The resulting model for figure detection is given by ()[model_extract_figures.pt].
From these approximately 1700 book pages 250 contain figures that have been annotated with bounding boxes with the image annotation webservice [CVAT](https://www.cvat.ai/). Training has been done locally with the nano version of YOLOv8. The resulting model for figure detection is given by [model_extract_figures.pt](model_extract_figures.pt).
