README.md

metadata

library_name: Doc-UFCN
license: mit
tags:
  - Doc-UFCN
  - PyTorch
  - object-detection
  - dla
  - historical
  - handwritten
metrics:
  - IoU
  - F1
  - [email protected]
  - [email protected]
  - 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!

@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    title = {{Robust Text Line Detection in Historical Documents: Learning and Evaluation Methods}},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}
}