This is the repository for our Signal, Image and Video course Project (Giovanni Valer and Laurence Bonat).
The Report is available here.
We used Python 3.12.0 and Tesseract-OCR 5.3.3. See requirements.txt for the required packages.
The methods
folder contains the different experiments of our project.
There are different functionalities:
manual_trackbar.py
: trackbar in manual modeautonomous_trackbar.ipynb
: trackbar in autonomous modeautomatic_filtering.ipynb
: automatic filtering of the text through a specific pipelinelines_detection.ipynb
: automatically detect if a text is on lined/squared papersquared_paper_ocr.ipynb
: HTR on lined/squared paper
In results
are the results of all methods.
There is the compute_metrics.py
script which automatically computes and saves the average accuracy of each method in results/results.txt
, (plus some other metrics in results/metrics
).