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CRNN with CTC-Loss

Deep Learning Project with 2 neural networks, CNN-1D-LSTM-ctc/CNN-2D-LSTM-ctc, for handwritten text recognition.

MD-LSTM Implementation is from https://github.com/philipperemy/tensorflow-multi-dimensional-lstm.

The dataloader is from https://github.com/githubharald/SimpleHTR.

Data used for training is the IAM-Words database.

This project is done as part of my studies.

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── model             <- Trained and serialized models, model predictions, or model summaries
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── src                <- Source code for use in this project.
│
└── tox.ini            <- tox file with settings for running tox; see tox.testrun.org

Project based on the cookiecutter data science project template. #cookiecutterdatascience