lquirosd / P2pala
Licence: gpl-3.0
Page to PAGE Layout Analysis Tool
Stars: ✭ 147
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python
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P2PaLA
Page to PAGE Layout Analysis (P2PaLA) is a toolkit for Document Layout Analysis based on Neural Networks.
💥 Try our new DEMO for online baseline detection. ❗️❗️
If you find this toolkit useful in your research, please cite:
@misc{p2pala2017,
author = {Lorenzo Quirós},
title = {P2PaLA: Page to PAGE Layout Analysis tookit},
year = {2017},
publisher = {GitHub},
note = {GitHub repository},
howpublished = {\url{https://github.com/lquirosd/P2PaLA}},
}
Check this paper for more details Arxiv.
Requirements
- Linux (OSX may work, but untested.).
- Python (2.7, 3.6 under conda virtual environment is recomended)
- Numpy
- PyTorch (1.0). PyTorch 0.3.1 compatible on this branch
- OpenCv (3.4.5.20).
- NVIDIA GPU + CUDA CuDNN (CPU mode and CUDA without CuDNN works, but is not recomended for training).
-
tensorboard-pytorch (v0.9) [Optional].
pip install tensorboardX> A diferent conda env is recomended to keep tensorflow separated from PyTorch
Install
python setup.py install
To install python dependencies alone, use requirements file
conda env create --file conda_requirements.yml
Usage
- Input data must follow the folder structure
data_tag/page, where images must be into thedata_tagfolder and xml files intopage. For example:
mkdir -p data/{train,val,test,prod}/page;
tree data;
data
├── prod
│ ├── page
│ │ ├── prod_0.xml
│ │ └── prod_1.xml
│ ├── prod_0.jpg
│ └── prod_1.jpg
├── test
│ ├── page
│ │ ├── test_0.xml
│ │ └── test_1.xml
│ ├── test_0.jpg
│ └── test_1.jpg
├── train
│ ├── page
│ │ ├── train_0.xml
│ │ └── train_1.xml
│ ├── train_0.jpg
│ └── train_1.jpg
└── val
├── page
│ ├── val_0.xml
│ └── val_1.xml
├── val_0.jpg
└── val_1.jpg
- Run the tool.
python P2PaLA.py --config config.txt --tr_data ./data/train --te_data ./data/test --log_comment "_foo"
❗️ Pre-trained models available here
- Use TensorBoard to visualize train status:
tensorboard --logdir ./work/runs
- xml-PAGE files must be at "./work/results/test/"
We recommend Transkribus or nw-page-editor to visualize and edit PAGE-xml files.
- For detail about arguments and config file, see docs or
python P2PaLa.py -h. - For more detailed example see egs:
License
GNU General Public License v3.0 See LICENSE to see the full text.
Acknowledgments
Code is inspired by pix2pix and pytorch-CycleGAN-and-pix2pix
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].