text-quality 0.1.5

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

Text Quality

This package determines the quality of a (digitized) page in terms of text quality.

Usage

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'.
(lahter) carstenschnober@Carstens-MacBook-Pro htr-quality-classifier % 

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.

How to use text_quality

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

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 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 .

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.

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