Metadata-Version: 2.0
Name: kraken
Version: 0.7.3
Summary: OCR engine compatible with ocropus
Home-page: http://kraken.re
Author: Benjamin Kiessling
Author-email: mittagessen@l.unchti.me
License: Apache
Keywords: ocr
Requires-Dist: future
Requires-Dist: requests
Requires-Dist: click (>=5.0)
Requires-Dist: dominate
Requires-Dist: numpy
Requires-Dist: Pillow
Requires-Dist: regex
Requires-Dist: scipy
Requires-Dist: protobuf

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

.. image:: https://travis-ci.org/mittagessen/kraken.svg
    :target: https://travis-ci.org/mittagessen/kraken

kraken is a fork of ocropus intended to rectify a number of issues while
preserving (mostly) functional equivalence. Its main goals are:

  - Explicit input/output handling ✓
  - Clean public API 
  - Word and character bounding boxes in hOCR ✓
  - Tests
  - Removal of runtime dependency on gcc ✓
  - `clstm <https://github.com/tmbdev/clstm>`_ compatibility ✓

Ticked of goals have been realized while some others still require further
work. Pull requests and code contributions are always welcome.

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

While kraken does not require a working C compiler on run-time anymore numpy
and scipy compilation still requires build-essential or your distributions
equivalent. Because the build behavior of pip versions older than 6.1.0
interferes with the scipy build process numpy has to be installed before doing
the actual install:

::

  # pip install numpy

If ``clstm`` support is desired (highly recommended) the associated python
extension has to be build and installed.

Install kraken either from pypi:

::

  $ pip install kraken

or by running pip in the git repository:

::

  $ pip install .

Finally you'll have to scrounge up an RNN to do the actual recognition of
characters. To download ocropus' default RNN and place it in the kraken
directory for the current user:

::

  $ kraken get default

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

To binarize a single image using the nlbin algorithm:

::

  $ kraken -i image.tif bw.tif binarize

To segment a binarized image into reading-order sorted lines:

::

  $ kraken -i bw.tif lines.txt segment bw.png

To OCR a binarized image using the default RNN and the previously generated
page segmentation:

::

  $ kraken -i bw.tif image.txt ocr --lines lines.txt

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

Have a look at the `documentation <http://kraken.re>`_



