This repository implements the optical character recognition (OCR), natural-language processing (NLP) and topic modeling of historical organic periodicals.
- python 3.6+
- tesseract-ocr (https://github.com/tesseract-ocr/tesseract)
- imagemagick
- nltk
- scikit-learn
- jupyter
- pyLDAvis (for visualizing models)
I recommend using virtualenv/virtualenvwrapper to install/manage the python modules.
Use Pip to install directly from GitHub.
pip install git+https://github.com/cloudbopper/perysis.git@master#egg=perysis
Add '-e' for an editable install.
Preprocessing OCR-ed text
python -m perysis.preprocess -input_dir documents_raw -output_dir documents_processed
periodicals-analysis is free, open source software, released under the MIT license. See LICENSE for details.