Metadata-Version: 1.1
Name: yayi
Version: 0.8.8.dev
Summary: Yayi toolbox for image processing and mathematical morphology
Home-page: http://raffi.enficiaud.free.fr
Author: Raffi Enficiaud
Author-email: raffi.enficiaud@free.fr
License: Boost Software License - Version 1.0 - August 17th, 2003
Description: Yayi
        ====
        
        Image processing and mathematical morphology framework in C++ and Python.
        
        Yayi is a open-source image processing framework with a focus on Mathematical Morphology. 
        
        The core of Yayi is entirely written in C++, mainly using template code which enables a high level of 
        genericity. It implements some of the main concepts of Mathematical Morphology into an efficient and proven design. 
        Yayi aims at providing robust, efficient and flexible algorithms for image analysis, but also reference algorithms 
        for Mathematical Morphology.
        
        The python interface provides a simple way for using the main notions and functions of mathematical morphology. 
        The export uses the boost.python framework.
        
        The whole project uses `cmake`_ for building. Some bindings with `setup.py` are being developed in order to be able 
        to just `pip install yayi`.
        
        It is released under the very permissive Boost license. 
        
        .. _boost: http://www.boost.org
        
        .. _cmake: http://www.cmake.org
        
        
        Key features
        ------------
        
        * Image I/O: png (8/16/32), tiff (8/16/32), jpeg, hfd5
        * Image arithmetic, pixel-wise comparisons, logical combinations
        * Color space transformation (xyY, XYZ, LAB, YUV, etc)
        * structuring element creation
        * Basic mathematical morphology: erosion, dilation, opening, closing (grey scale), hit-or-miss, white/black hat
        * connected components labeling (background, adjacency graph...), measures on connected components
        * morphological reconstruction and levelings
        * segmentation: watershed transform
        
        
        
        Installation
        ------------
        Yayi needs `boost`_, `cmake`_ and a decent C++ compiler to build. You should install those tools in your system, preferably
        using your package manager.
        
        .. warning:: as soon as you build and install Yayi, Yayi becomes dependent on the `boost` package. If you upgrade `boost`
           to a new version, then it might break Yayi. As a matter of fact, python package management does not communicate
           with the /native/ package management of your operating system.  
           
        
        .. note:: some of the dependencies are shipped with Yayi directly, but on some platforms (Linux) the dependencies provided
                  by the package manager are preferred.
                  
        After the installation, the following code should work: 
        
        .. code:: python
        
           import yayi
           yayi.IO.readPNG('my/png/file.png")
        
        .. note:: currently not compiling the Python extensions with the HDF5 support.
        
        Linux Ubuntu
        ~~~~~~~~~~~~
        Ubuntu is shipped with its own package manager, and it is straightforward to install packages. An Ubuntu packate is under
        development, but currently Yayi needs to be built from the sources.
        
        To install the dependencies of Yayi, type the following in a Terminal:
        
        .. code:: shell
        
          sudo apt-get install boost, cmake, python-numpy, python-pip, libjpeg8-dev, zlib1g-dev, libpng12-dev, libtiff4-dev, libhdf5-dev
        
        and then just type (and wait)
        
        .. code:: shell
        
          pip install yayi
        
        
        OSX
        ~~~
        On OSX, a wheel package is provided and it contains all the dependencies (especially boost). If you are lucky
        the wheel is for your specific version of OSX/Python. If you are less lucky you should build Yayi from the sources.
        For that, first install the dependencies with eg.`brew`_   
        
        .. code:: shell
        
          brew install boost
          brew install cmake
        
        and then just type the following (and wait):
        
        .. code:: shell
        
          # numpy should be installed on a default Mac
          pip install numpy
          pip install yayi
        
        
        Win32
        ~~~~~
        
        On Windows, binary packages (installer and wheel package) are provided, but for Python 2.7 64-bits only. If this is not your version of Python/Win architecture, 
        then you need to build Yayi on your platform like the other platforms. However, you are kind of lucky because you are not obliged to use a specific
        toolchain for that (so you can build yayi with Visual 2013 community and you are not obliged to have Visual 2008 or some obsolete toolchain). 
        
        If you need to build Yayi, first install `cmake`_ and a binary version of `boost`_ (or build it yourself). Then you have two options:
        
        * build yayi with `setup.py`
        * build yayi from `pip`
        
        With `setup.py`, extract the source and then type (and wait)
        
        .. code:: shell
        
          python setup.py build_cmake --boostroot=/my_boost/installation/location/boost_1_55/ install
        
        With `pip`, this is almost the same, you have to pass the previous option like this:
        
        .. code:: shell
        
          pip install --upgrade --install-option "build_cmake" --install-option "--boostroot=/my_boost/installation/location/boost_1_55/" yayi-XXXX.tar.gz
        
        
Keywords: image processing,mathematical morphology,multidimensional images,multispectral images,image segmentation,erosion,dilation,opening,closing,hit-or-miss,connected components
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows :: Windows NT/2000
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Mathematics
