mikegerber/ocrd_typegroups_classifier

ocrd_typegroups_classifier

Typegroups classifier for OCR

Quick setup

If needed, create a virtual environment for Python 3 (it was tested successfully with Python 3.7), activate it, and install ocrd.

virtualenv -p python3 ocrd-venv3
source ocrd-venv3/bin/activate
pip3 install ocrd

Enter in the folder containing the tool: cd ocrd_typegroups_classifier/

Install the module and its dependencies

make install
make deps

Finally, run the test:

sh test/test.sh

** Important: ** The test makes sure that the system does work. For speed reasons, a very small neural network is used and applied only to the top-left corner of the image, therefore the quality of the results will be of poor quality.

Models

The model classifier-1.tgc is based on a ResNet-18, with less neurons per layer than the usual model. It was briefly trained on 12 classes: Adornment, Antiqua, Bastarda, Book covers and other irrelevant data, Empty Pages, Fraktur, Griechisch, Hebräisch, Kursiv, Rotunda, Textura, and Woodcuts - Engravings.

Heatmap Generation

Given a trained model, it is possible to produce heatmaps corresponding to classification results. Syntax:

python3 tools/heatmap.py ocrd_typegroups_classifier/models/classifier.tgc sample.jpg out