Implementation of a model for handwriting synthesis using Long Short-Term Memory recurrent neural networks in PyTorch. Based on the work of Alex Graves described in this article: https://arxiv.org/abs/1308.0850
The dataset used to train this neural network is the IAM On-Line Handwriting Database. In order to train this network you have to register and download the following files:
And the directory structure has to be the following:
.
├── main.py
├── README.md
├── parameters.yaml
├── LICENSE
├── trained_models # Trained models
├── src # Source files
└── data # Data files
├── ascii # text files that contain the written text
| ├── a01
| | ├── a01-000
| | | ├── a01-000u.txt
| | | └── a01-000x.txt
| | └── ...
| └── ...
└── lineStrokes # xml files that contain the strokes
├── a01
| ├── a01-000
| | ├── a01-000u-01.xml
| | └── a01-000u-02.xml
| | └── ...
| └── ...
└── ...
Create virtual environment and install packages:
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
See the main script's help text for more information:
python main.py --help