Doc-UFCN - Generic Samaritan manuscripts line detection
The generic Samaritan manuscripts line detection model predicts text lines from document images.
Model description
It has been trained on images with their largest dimension equal to 768 pixels, keeping the original aspect ratio.
How to use?
Please refer to the Doc-UFCN library page (https://pypi.org/project/doc-ufcn/) to use this model.
Cite us!
@inproceedings{boillet2022,
author = {Boillet, Mélodie and Kermorvant, Christopher and Paquet, Thierry},
title = {{Robust Text Line Detection in Historical Documents: Learning and Evaluation Methods}},
booktitle = {{International Journal on Document Analysis and Recognition (IJDAR)}},
year = {2022},
month = Mar,
pages = {1433-2825},
doi = {10.1007/s10032-022-00395-7}
}
@inproceedings{boillet2020,
author = {Boillet, Mélodie and Kermorvant, Christopher and Paquet, Thierry},
title = {{Multiple Document Datasets Pre-training Improves Text Line Detection With
Deep Neural Networks}},
booktitle = {2020 25th International Conference on Pattern Recognition (ICPR)},
year = {2021},
month = Jan,
pages = {2134-2141},
doi = {10.1109/ICPR48806.2021.9412447}
}
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the HF Inference API does not support Doc-UFCN models with pipeline type image-segmentation