Metadata-Version: 2.1
Name: imreg-dft
Version: 2.0.0
Summary: Image registration utility using algorithms based on discrete Fourier transform (DFT, FFT)
Home-page: https://github.com/matejak/imreg_dft
Author: Matěj Týč
Author-email: matej.tyc@gmail.com
License: BSD
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Topic :: Utilities
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: BSD License
Requires-Dist: setuptools (>=1.0)
Requires-Dist: numpy (>=1.7)
Requires-Dist: scipy (>=0.12)
Requires-Dist: pillow
Provides-Extra: better_performance
Requires-Dist: pyfftw (>=0.9); extra == 'better_performance'
Provides-Extra: loading_images
Requires-Dist: pillow (>=2.2); extra == 'loading_images'
Provides-Extra: plotting
Requires-Dist: matplotlib (>=1.2); extra == 'plotting'

General overview
================

``imreg_dft`` is your first-choice Python image registration utility.
In plain language, it implements means of guessing translation, rotation and scale variation between two images.
The name comes from the fact that it doesn't work with those images directly, but it works with their spectrum (DFT using FFT), and its log-polar transformation [1]_, hence the ``_dft`` after ``imreg``.

Basically, if you want to align two images that have different scale and are rotated and shifted against each other, ``imreg_dft`` is the tool you want to check out.
`Get started <http://pythonhosted.org/imreg_dft/quickstart.html#quickstart>`_ in five minutes and see how it works for you!

:Authors:
  - `Matěj Týč <https://github.com/matejak>`_ `PGP public key <https://keyserver.mattrude.com/pks/lookup?op=get&search=0x607524F854FD905F>`_
  - `Christoph Gohlke <http://www.lfd.uci.edu/~gohlke/>`_

:Organization:
  - Brno University of Technology, Brno, Czech Republic
  - Laboratory for Fluorescence Dynamics, University of California, Irvine

:Copyright:
  - 2014-2015, Matěj Týč
  - 2011-2014, Christoph Gohlke

.. _requirements:

Requirements
------------

``imreg_dft`` is `free software <http://en.wikipedia.org/wiki/Free_software>`_, i.e. both free of charge (so it is free as free beer) and you as a user are granted `four basic freedoms <https://www.gnu.org/philosophy/free-sw.html>`_ (so it is also free as free speech).

Generally, you will need ``numpy`` and ``scipy`` for the algorithm functionality and ``matplotlib`` for plotting.
For the command-line tool, reading images is useful, so make sure you have ``pillow`` (or ``PIL``, which is deprecated).

Quickstart
----------

Check the documentation on `readthedocs.ort <http://imreg-dft.readthedocs.org/en/latest/quickstart.html>`_ (bleeding-edge) or `pythonhosted.org <http://pythonhosted.org/imreg_dft/quickstart.html>`_ (with images).
Or even better, generate the documentation yourself! 

1. Install the package by running ``python setup.py install`` in the project root.
#. Install packages that are required for the documentation to compile (see the ``requirements_docs.txt`` file.
#. Go to the ``doc`` directory and run ``make html`` there.
   The documentation should appear in the ``_build`` subfolder, so you may open ``_build/html/index.html`` with your web browser to see it.

Notes
-----

``imreg_dft`` is based on the `code <http://www.lfd.uci.edu/~gohlke/code/imreg.py.html>`_ by Christoph Gohlke.

References
----------
.. [1] An FFT-based technique for translation, rotation and scale-invariant
    image registration. BS Reddy, BN Chatterji.
    IEEE Transactions on Image Processing, 5, 1266-1271, 1996


