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---
library_name: Doc-UFCN
license: mit
tags:
- Doc-UFCN
- PyTorch
- object-detection
- dla
- historical
- handwritten
metrics:
- IoU
- F1
- AP@.5
- AP@.75
- AP@[.5,.95]
pipeline_tag: image-segmentation
---
# 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!
```bibtex
@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title = {{Robust Text Line Detection in Historical Documents: Learning and Evaluation Methods}},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}
}
```
```bibtex
@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}
}
```
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