The official GitHub repository for the paper on DocSynth: A Layout Guided Approach for Controllable Document Image Synthesis
16th ICDAR 2021 (Lausanne, Switzerland).
The work will feature inGetting Started
Step 1: Clone this repository and change directory to repository root
git clone https://github.com/biswassanket/synth_doc_generation.git
cd synth_doc_generation
Step 2: Make sure you have conda installed. If you do not have conda, here's the magic command to install miniconda.
curl -o ./miniconda.sh -O https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
chmod +x ./miniconda.sh
./miniconda.sh -b -u -p .
Step 3: Create an environment to run the project and install required dependencies.
- To create conda environment:
conda env create -f environment.yml
Step 4: Activate the conda environment
conda activate layout2im
Step 5: Downloading Dataset
- To download PubLayNet dataset:
curl -o <YOUR_TARGET_DIR>/publaynet.tar.gz https://dax-cdn.cdn.appdomain.cloud/dax-publaynet/1.0.0/publaynet.tar.gz
Step 5: Downloading the trained models
- Download the trained models to
checkpoints/pretrained/
.
Step 6: Testing
Testing on PubLayNet dataset:
$ python layout2im/test.py --dataset publaynet --coco_dir datasets/publaynet \
--saved_model checkpoints/pretrained/publaynet_netG.pkl \
--results_dir checkpoints/pretrained_results_publaynet
Step 7: Training
$ python layout2im/train.py
Results
1. T-SNE Visualization of Synthetic Document Images
2. Diverse results generated from the same document layout
3. Examples of interactive generation of documents by the user
Citation
If you find this code useful in your research then please cite
@inproceedings{biswas2021docsynth,
title={DocSynth: A Layout Guided Approach for Controllable Document Image Synthesis},
author={Biswas, Sanket and Riba, Pau and Llad{\'o}s, Josep and Pal, Umapada},
booktitle={International Conference on Document Analysis and Recognition (ICDAR)},
year={2021}
}
Acknowledgement
Our project has adapted and borrowed the code structure from layout2im. We thank the authors. This research has been partially supported by the Spanish projects RTI2018-095645-B-C21, and FCT-19-15244, and the Catalan projects 2017-SGR-1783, the CERCA Program / Generalitat de Catalunya and PhD Scholarship from AGAUR (2021FIB-10010).
Authors
Conclusion
Thank you and sorry for the bugs!