Presentation

ajmc is work-in-progress python package containing the tools developped for the AjaxMultiCommentary project.

The project starts from images of classical commentaries and deals with OCR, OLR, and further NLP tasks such as NER and reference resolution.

These steps are covered by the ajmc's sub-packages:

• ajmc.commons contains shared tools and variables.
• ajmc.corpora contains tools to deal with the project's corpora.
• ajmc.nlp contains helpers for named entity recognition with HuggingFace transformers.
• ajmc.ocr contains helpers and functions to run tesseract and perform coordinate-based evaluation of OCR outputs.
• ajmc.olr contains helpers and function to perform layout analysis with YOLOv5 and LayoutLM, as well preparing layout annotation with VIA2.
• ajmc.text_processing offers a general framework to deal with ocr-output and store them as canonical jsons.

For a more detailed description of the codebase's architecture and innerworkings, please refer to the documentation. Introductory notebooks provided in the docs can also be found in docs/other_pages

Setup

Install from source

Please install ajmc using git clone https://github.com/AjaxMultiCommentary/ajmc. setup.py lists all the required dependencies. For collaborative development, please use a dedicated virtual environment (for instance with conda).

Install with PIP

python -m pip install git+'https://github.com/AjaxMultiCommentary/ajmc'

Running tests

Make sure that you have a local virtualenv activated and pytest installed.

You can then run all tests by invoking:

$ python -m pytest

You can also test a single file (or a single test --- see the pytest docs):

$ python -m pytest "ajmc/search/index.py"

Acknowledgements

Code in this repository was produced in the context of the Ajax Multi-Commentary project, funded by the Swiss National Science Foundation under an Ambizione grant PZ00P1_186033.