/Handwriting-Model

Implementation of a network for handwriting synthesis based on the work of Graves et al. described in this article: https://arxiv.org/abs/1308.0850 (WIP)

Primary LanguagePythonMIT LicenseMIT

Handwriting Model

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

Dataset

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
            |   |   └── ...
            |   └── ...
            └── ...

Usage

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