khanhnn00 / paddle-ocr Goto Github PK

• Contents
  • Introduction
  • Requirements
  • Usage
  • Citations
  • License
  • Acknowledgements

Just for fun.

• python = 3.6
• torchvision = 0.6.1
• tabulate = 0.8.7
• overrides = 3.0.0
• opencv_python = 4.3.0.36
• numpy = 1.16.4
• pandas = 1.0.5
• allennlp = 1.0.0
• torchtext = 0.6.0
• tqdm = 4.47.0
• torch = 1.5.1shapely
• scikit-image
• imgaug==0.4.0
• pyclipper
• lmdb
• tqdm
• numpy
• visualdl
• python-Levenshtein
• opencv-contrib-python==4.4.0.46
• cython
• lxml
• premailer
• openpyxl
• paddle

pip install -r requirements.txt

Are you having fun with installing the required environment variables? Here's a good news: besides the above stuffs, you also have to install paddle-gpu (by visiting this link)

In order to run smoothly, you have to:

• Configurating your weight and dataset folders in config.yml file. (for each module please read the README file in that folder)
• Run the predictor.py file

If you find this code useful please cite the authors, not us (we just reimplement)

• paper:

@inproceedings{Yu2020PICKPK,
  title={{PICK}: Processing Key Information Extraction from Documents using 
  Improved Graph Learning-Convolutional Networks},
  author={Wenwen Yu and Ning Lu and Xianbiao Qi and Ping Gong and Rong Xiao},
  booktitle={2020 25th International Conference on Pattern Recognition (ICPR)},
  year={2020}
}

• PaddleOCR

• Many thanks to Khanh Tran and Karl Horky for contributing and revising the English documentation.
• Many thanks to zhangxin for contributing the new visualize function、add .gitignore and discard set PYTHONPATH manually.
• Many thanks to lyl120117 for contributing the code for printing the network structure.
• Thanks xiangyubo for contributing the handwritten Chinese OCR datasets.
• Thanks authorfu for contributing Android demo and xiadeye contributing iOS demo, respectively.
• Thanks BeyondYourself for contributing many great suggestions and simplifying part of the code style.
• Thanks tangmq for contributing Dockerized deployment services to PaddleOCR and supporting the rapid release of callable Restful API services.
• Thanks lijinhan for contributing a new way, i.e., java SpringBoot, to achieve the request for the Hubserving deployment.
• Thanks Mejans for contributing the Occitan corpus and character set.
• Thanks LKKlein for contributing a new deploying package with the Golang program language.
• Thanks Evezerest, ninetailskim, edencfc, BeyondYourself and 1084667371 for contributing a new data annotation tool, i.e., PPOCRLabel。

This project is licensed under the MIT License. See LICENSE for more details.

This project structure takes example by PyTorch Template Project.