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fieldextractor's Introduction

Field Extraction from Forms

Introduction

This repository contains code of Field Extraction from Forms with Unlabeled Data.

Environment

CUDA="11.0"
CUDNN="8"
UBUNTU="18.04"

Install

bash install.sh
# under our project root folder
python setup.py develop 

Data Preparation

*We have pre-processed INV-CDIP test set under datasets/.

Reproduce Our Results

*Download our model pre-trained using INV-CDIP unlabeled train set.

python main.py \
--model_name_or_path pretrained_model_acl2022 \
--output_dir $OUTPUT_PATH

Visualization

*Download images of INV-CDIP test set and put under datasets/imgs.

python vis_results.py --pred_path $OUTPUT_PATH/prediction_pairs.pkl

Citation

If you find this codebase useful, please cite our paper:

@article{gao2021field,
  title={Field Extraction from Forms with Unlabeled Data},
  author={Gao, Mingfei and Chen, Zeyuan and Naik, Nikhil and Hashimoto, Kazuma and Xiong, Caiming and Xu, Ran},
  journal={ACL Spa-NLP Workshop},
  year={2022}
}

License

Our code is released under BSD 3-Clause.

Our pre-trained model is released under CC BY-NC 4.0.

The INV-CDIP dataset is released under CC BY-NC 4.0. The underlying documents to which the dataset refers are from the Tobacco Collections of Industry Documents Library. Please see Copyright and Fair Use for more information.

Contact

Please send an email to [email protected] if you have questions.

fieldextractor's People

Contributors

dependabot[bot] avatar mingfei-gao avatar

Stargazers

 avatar Ran Xu avatar  avatar Zeyuan Chen avatar  avatar

Watchers

Caridy Patiño avatar James Cloos avatar Demian Brecht avatar  avatar

Forkers

isabella232

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