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.. figure:: http://danschef.gitext.gfz-potsdam.de/arosics/images/arosics_logo.png
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        :target: https://gitext.gfz-potsdam.de/danschef/arosics
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An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data


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* Free software: GNU General Public License v3
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* Documentation: http://danschef.gitext.gfz-potsdam.de/arosics/doc/

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Status
------

.. .. image:: https://img.shields.io/travis/danschef/arosics.svg
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        :target: https://travis-ci.org/danschef/arosics

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.. .. image:: https://readthedocs.org/projects/arosics/badge/?version=latest
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        :target: https://arosics.readthedocs.io/en/latest/?badge=latest
        :alt: Documentation Status

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.. .. image:: https://pyup.io/repos/github/danschef/arosics/shield.svg
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     :target: https://pyup.io/repos/github/danschef/arosics/
     :alt: Updates


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.. image:: https://gitext.gfz-potsdam.de/danschef/arosics/badges/master/build.svg
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        :target: https://gitext.gfz-potsdam.de/danschef/arosics/commits/master
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.. image:: https://gitext.gfz-potsdam.de/danschef/arosics/badges/master/coverage.svg
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        :target: http://danschef.gitext.gfz-potsdam.de/arosics/coverage/
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.. image:: https://img.shields.io/pypi/v/arosics.svg
        :target: https://pypi.python.org/pypi/arosics
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.. image:: https://img.shields.io/pypi/l/arosics.svg
        :target: https://gitext.gfz-potsdam.de/danschef/arosics/blob/master/LICENSE
.. image:: https://img.shields.io/pypi/pyversions/arosics.svg
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        :target: https://img.shields.io/pypi/pyversions/arosics.svg
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See also the latest coverage_ report and the nosetests_ HTML report.
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Features
--------

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* Detection and correction of local or global geometric displacements between two input images.
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Installation
------------

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AROSICS depends on some open source packages which are usually installed without problems by the automatic install
routine. However, for some projects, we strongly recommend resolving the dependency before the automatic installer
is run. This approach avoids problems with conflicting versions of the same software.
Using conda_, the recommended approach is:

 .. code-block:: console

    # create virtual environment for arosics, this is optional
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    conda create --name arosics python=3
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    source activate arosics
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    conda install -c conda-forge numpy gdal scikit-image matplotlib pyproj rasterio shapely geopandas cmocean
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    # optional libraries:
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    conda install -c conda-forge basemap pykrige
    conda install -c conda-forge pyfftw  # Linux and MacOS
    conda install -c jesserobertson pyfftw  # Windows
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To install AROSICS, use the pip installer:

 .. code-block:: console
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    pip install arosics
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Or clone the repository via GIT and update the PATH environment variable:
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 .. code-block:: console
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    cd /your/installation/folder
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    git clone https://gitext.gfz-potsdam.de/danschef/arosics.git
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    git clone https://gitext.gfz-potsdam.de/danschef/geoarray.git
    git clone https://gitext.gfz-potsdam.de/danschef/py_tools_ds.git
    PATH=$PATH:/path/to/your/installation/folder/arosics:/path/to/your/installation/folder/geoarray:/path/to/your/installation/folder/py_tools_ds
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Credits
-------

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AROSICS was developed within the context of the GeoMultiSens project funded by the German Federal Ministry
of Education and Research (project grant code: 01 IS 14 010 A-C).

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This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
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The test data represent modified Copernicus Sentinel data (2016).
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.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
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.. _coverage: http://danschef.gitext.gfz-potsdam.de/arosics/coverage/
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.. _nosetests: http://danschef.gitext.gfz-potsdam.de/arosics/nosetests_reports/nosetests.html
.. _conda: https://conda.io/docs/
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