kraken

OCR engine for all the languages

Science Score: 67.0%

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CITATION.cff file
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.zenodo.json file
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Found 1 DOI reference(s) in README
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Links to: zenodo.org
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Scientific vocabulary similarity
Low similarity (14.9%) to scientific vocabulary

Keywords

alto-xml handwritten-text-recognition hocr htr layout-analysis neural-networks ocr optical-character-recognition page-xml

Last synced: 6 months ago · JSON representation ·

Repository

OCR engine for all the languages

Basic Info

Host: GitHub
Owner: mittagessen
License: apache-2.0
Language: Python
Default Branch: main
Homepage: http://kraken.re
Size: 29.6 MB

Statistics

Stars: 870
Watchers: 30
Forks: 148
Open Issues: 32
Releases: 13

Topics

alto-xml handwritten-text-recognition hocr htr layout-analysis neural-networks ocr optical-character-recognition page-xml

Created almost 11 years ago · Last pushed 6 months ago

Metadata Files

Readme License Citation

README.rst

Description
===========

.. image:: https://github.com/mittagessen/kraken/actions/workflows/test.yml/badge.svg
    :target: https://github.com/mittagessen/kraken/actions/workflows/test.yml

kraken is a turn-key OCR system optimized for historical and non-Latin script
material.

kraken's main features are:

  - Fully trainable layout analysis, reading order, and character recognition
  - `Right-to-Left `_, `BiDi
    `_, and Top-to-Bottom
    script support
  - `ALTO `_, PageXML, abbyyXML, and hOCR
    output
  - Word bounding boxes and character cuts
  - Multi-script recognition support
  - `Public repository `_ of model files
  - Variable recognition network architecture

Installation
============

Kraken can be run on Linux or Mac OS X (both x64 and ARM). Installation is
through the on-board *pip* utility. To not pollute the global state of your
distribution's package manager it is recommended to use virtual environments.
If you do not have a setup or do not wish to handle virtual environments
yourself you can use `pipx`.

.. code-block:: console

   $ sudo apt install pipx
   $ pipx install kraken

kraken works both on Linux and Mac OS X and with any python interpreter between
3.9 and 3.11. It is possible the installation fails because `pipx` defaults to
an unsupported interpreter version. In that case you need to install a
compatible interpreter version such as 3.11 and then specify this version
explicitly:

.. code-block:: console

   $ sudo apt install python3.11-full
   $ pipx install --python python3.11 kraken


Installation using pip
----------------------

Create and activate a separate virtual environment using whatever tool you
like.

.. code-block:: console

  $ pip install kraken

or by running pip in the git repository:

.. code-block:: console

  $ pip install .

If you want direct PDF and multi-image TIFF/JPEG2000 support it is necessary to
install the `pdf` extras package for PyPi:

.. code-block:: console

   $ pip install kraken[pdf]

Finally you'll have to scrounge up a model to do the actual recognition of
characters. To download the default model for printed French text and place it
in the kraken directory for the current user:

::

  $ kraken get 10.5281/zenodo.10592716

A list of libre models available in the central repository can be retrieved by
running:

::

  $ kraken list

Quickstart
==========

Recognizing text on an image using the default parameters including the
prerequisite steps of binarization and page segmentation:

::

  $ kraken -i image.tif image.txt binarize segment ocr

To binarize a single image using the nlbin algorithm:

::

  $ kraken -i image.tif bw.png binarize

To segment an image (binarized or not) with the new baseline segmenter:

::

  $ kraken -i image.tif lines.json segment -bl


To segment and OCR an image using the default model(s):

::

  $ kraken -i image.tif image.txt segment -bl ocr -m catmus-print-fondue-large.mlmodel

All subcommands and options are documented. Use the ``help`` option to get more
information.

Documentation
=============

Have a look at the `docs `_.

Related Software
================

These days kraken is quite closely linked to the `eScriptorium
`_ project developed in the same eScripta research
group. eScriptorium provides a user-friendly interface for annotating data,
training models, and inference (but also much more). There is a `gitter channel
`_ that is mostly intended for
coordinating technical development but is also a spot to find people with
experience on applying kraken on a wide variety of material.

Funding
=======

kraken is developed at the `École Pratique des Hautes Études `_, `Université PSL `_.

.. container:: twocol

   .. container::

        .. image:: https://raw.githubusercontent.com/mittagessen/kraken/main/docs/_static/normal-reproduction-low-resolution.jpg
          :width: 100
          :alt: Co-financed by the European Union

   .. container::

        This project was funded in part by the European Union. (ERC, MiDRASH,
        project number 101071829).

.. container:: twocol

   .. container::

        .. image:: https://raw.githubusercontent.com/mittagessen/kraken/main/docs/_static/normal-reproduction-low-resolution.jpg
          :width: 100
          :alt: Co-financed by the European Union

   .. container::

        This project was partially funded through the RESILIENCE project, funded from
        the European Union’s Horizon 2020 Framework Programme for Research and
        Innovation.


.. container:: twocol

   .. container::

      .. image:: https://projet.biblissima.fr/sites/default/files/2021-11/biblissima-baseline-sombre-ia.png
         :width: 400
         :alt: Received funding from the Programme d’investissements d’Avenir

   .. container::

        Ce travail a bénéficié d’une aide de l’État gérée par l’Agence Nationale de la
        Recherche au titre du Programme d’Investissements d’Avenir portant la référence
        ANR-21-ESRE-0005 (Biblissima+).

Owner

Login: mittagessen
Kind: user
Location: Paris
Company: École Pratique des Hautes Études, Aoroc

Website: http://l.unchti.me
Repositories: 31
Profile: https://github.com/mittagessen

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Kiessling"
  given-names: "Benjamin"
  orcid: "https://orcid.org/0000-0001-9543-7827"
title: "The Kraken OCR system"
version: 6.0
date-released: 2025-08-29
url: "https://kraken.re"

GitHub Events

Total

Issues event: 92
Watch event: 121
Delete event: 3
Issue comment event: 150
Push event: 106
Pull request review event: 1
Pull request review comment event: 2
Pull request event: 27
Fork event: 19
Create event: 9

Last Year

Issues event: 92
Watch event: 121
Delete event: 3
Issue comment event: 150
Push event: 106
Pull request review event: 1
Pull request review comment event: 2
Pull request event: 27
Fork event: 19
Create event: 9

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 104
Total pull requests: 41
Average time to close issues: 3 months
Average time to close pull requests: about 1 month
Total issue authors: 54
Total pull request authors: 14
Average comments per issue: 2.84
Average comments per pull request: 0.98
Merged pull requests: 19
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 44
Pull requests: 13
Average time to close issues: about 1 month
Average time to close pull requests: 27 days
Issue authors: 27
Pull request authors: 5
Average comments per issue: 1.45
Average comments per pull request: 0.23
Merged pull requests: 8
Bot issues: 0
Bot pull requests: 0

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Issue Authors

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Pull Request Authors

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Top Labels

Issue Labels

enhancement (1) beginner-friendly (1)

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- pypi 9,503 last-month

Total dependent packages: 6
Total dependent repositories: 24
Total versions: 100
Total maintainers: 2

pypi.org: kraken

OCR/HTR engine for all the languages

Homepage: https://kraken.re
Documentation: https://kraken.readthedocs.io/
License: Apache
Latest release: 5.3.0
published over 1 year ago

Versions: 100
Dependent Packages: 6
Dependent Repositories: 24
Downloads: 9,503 Last month

Rankings

Dependent packages count: 1.4%

Dependent repos count: 3.0%

Average: 3.2%

Downloads: 5.2%

Maintainers (2)

berkerpeksag ogl-iris