Text Quality

A package to determine the quality of a a digitized text, from a handwritten script or scanned print (HTR/OCR output).

The current pipeline is tuned on (historic) Dutch language, and will not perform well on other languages. However, the underlying model has been used for other (Germanic) languages, and can be adapted and applied to texts of other languages and time periods.

Examples

Good quality (not necessarily perfect):

Van
Malacca den 29 maart 1.
door zoo veel ruijmer handen te hebben,
[…]
Siac van waar op den 5=e deeser,
na onse verschijde adhortaties, is over
eeen gekomen
zoo meede van Siac

Bad quality:

uijtkoops --
winst suijverevense versis
e ee
,, 19
1 oe
na aftrek van
5 p:s C: Commiss:s
t 1a per 't geheel t p=s lb. off @'t geheeke
[…]

What's Missing

• Pipelines for languages other than historic Dutch
• Automatic training procedure for creating and update pipelines
• Additional features such as publication year.

See this notebook for a semi-automated pipeline creation process.

How to use text_quality

After installation, use the classify_text_quality.py script to classify PageXML or plain text files. For instance, if you want to classify all *.xml files in the pages/ directory, use the --glob argument:

classify_text_quality.py --glob "page/*.xml" --output classifications.csv --output-scores

Per input file, one output line is returned in CSV table format, along with the classification result:

1. Good quality
2. Medium quality
3. Bad quality

All supported parameters:

$ classify_text_quality.py --help
usage: Classify the quality of a (digitized) text. [-h] [--input [FILE ...]] [--pagexml [FILE ...]] [--pagexml-glob PATTERN] [--output FILE] [--output-scores]

options:
  -h, --help            show this help message and exit
  --output FILE, -o FILE
                        Output file; defaults to stdout.
  --output-scores       Output scores and text statistics.

Input:
  --input [FILE ...], -i [FILE ...]
                        Plain text file(s) to classify. Use '-' for stdin.
  --pagexml [FILE ...]  Input file(s) in PageXML format.
  --pagexml-glob PATTERN, --glob PATTERN
                        A pattern to find a set of PageXML files, e.g. 'pagexml/*.xml'.

Notes

The pipeline might emit warnings like this:

UserWarning: X does not have valid feature names, but MLPClassifier was fitted with feature names

This is due to the internals of the Scikit-Learn Pipeline object, and can safely be ignored.

The dependencies are pinned to specific versions. While this prevents implicit updated even for patch-level updated of required libraries, it prevents misleading warnings emitted by varying Scikit-Learn versions. Hence, requirement dependecies can be changed manually, if you are aware of these issues.

The project setup is documented in project_setup.md. Feel free to remove this document (and/or the link to this document) if you don't need it.

Installation

To install the text_quality package:

pip install -U text-quality

Alternatively, install the package from GitHub repository:

git clone https://github.com/LAHTeR/htr-quality-classifier.git
cd htr-quality-classifier
python3 -m pip install -U .

Documentation

Readthedocs

Contributing

If you want to contribute to the development of text_quality, have a look at the contribution guidelines.

Credits

Logic and implementation are based on Nautilus-OCR.

This package was created with Cookiecutter and the NLeSC/python-template.

Badges

(Customize these badges with your own links, and check https://shields.io/ or https://badgen.net/ to see which other badges are available.)

fair-software.eu recommendations
(1/5) code repository
(2/5) license
(3/5) community registry
(4/5) citation
(5/5) checklist
howfairis
Other best practices
Static analysis
Coverage
Documentation
GitHub Actions
Build
Citation data consistency
SonarCloud
MarkDown link checker