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Extracting content from spesific address books

Project description

historical-text-extraction (hte)

PyPI version

Package to extract text from historical documents. The package is written for personal use.

Installation

The current release from the PyPI repository:

pip install hte

The development version from GitHub with:

pip install git+ssh://git@github.com/eirikberger/hte.git

Note that it is nessecary with a SSH key for this approach to work.

Using it

Import the package

from hte import digitize

The basic setup is the following:

# Define class
book = digitize.Book("data/finnmark_1968.pdf", "books")

# Run methods on the class
book.CreateFolderStructure()
book.PdfImport(page_info=False, from_page=21, to_page=263)
book.Split(multiple_columns=True)
book.RunOCR(type="splits", export_image=False)
book.CombineCleanGroup(ocr_grouping=True, group_type='norway')
book.RegexStructure("norway")

Make sure to install the correct language package for Tesseract.

# Check languages already installed: 
tesseract --list-langs

# Languages available for installation
apt-cache search tesseract-ocr

# Install the Norwegian language pack
sudo apt-get install tesseract-ocr-nor

Extracting headers

Start by converting xml files to json. These files can be created by using the free software labelImg.

import os 
os.chdir('/home/eirikb/Desktop')
header = Headers('train', 2022)
header.runbbxConverting()

Then convert the json file to csv.

convertFromJson('/home/eirikb/Desktop/training_xml/json-bbox', 'xml')

Finally, read the concent of the boxes.

ReadBoxes('json-bbox/xml.csv', 'hordaland', 'train', print_images=True)

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