Metadata-Version: 1.1
Name: intelligent_tracker
Version: 0.1.1
Summary: Install intelligent_tracker
Home-page: https://github.com/davtoh/InteligentTracker
Author: David Toro
Author-email: davsamirtor@gmail.com
License: GPL v3
Description: 
        Intelligent Tracker  |build-status| |docs|
        =========================================================
        
        Overview
        ========
        
        This package provides an API and user interface for tracking objects using haarcascades, keypoints and
        other methods that will be integrated in the future.
        
        The purpose is to create a software to create smart cameras that can detect and follow people
        in a close environment composed of scenes and entries on them like doors or imaginary areas
        where people or objects can be counted or statistics can be obtained.
        
        For now the project is its early stages and the development until the objectives can be reach can take time.
        But for now it offers a demo in the main.py script which hopefully can convey the intend of the project and be useful to someone.
        That said, this code does not intent to compete against commercial software but rather complement them for integration
        with a CCTV system and to not obscure users of what information is being processed from them hence the GPL licence.
        
        Latest:
        
            - Documentation: http://intelligent-tracker.readthedocs.io/
            - Project Homepage: https://github.com/davtoh/intelligent-tracker
        
        Licence:
        
            GPL v3 Licence_
        
        Documentation
        =============
        
        For API documentation, usage and examples see files in the "documentation"
        directory.  The ".rst" files can be read in any text editor or being converted to
        HTML or PDF using Sphinx_. A HTML version will be available soon.
        
        Installation
        ============
        ``pip install intelligent-tracker`` should work for most users.
        
        The usual setup.py for Python_ libraries are used for the source distribution.
        But OpenCV must be installed separately usually compiled from source.
        
        To install OpenCV on windows without much hassle I recommend installing the binaries from
        the `Unofficial Windows Binaries for Python`_ and for Debian distributions I
        provide the bash `OpenCV linux installation`_ so that the user can compile
        openCV (it can take some time). Bear in mind that for Linux it downloads the
        latest 3.x version.
        
        Once successfully installed you can import it in python as:
        
            >>>> import intelligent_tracker as itt
        
        Releases
        ========
        
        All releases follow semantic rules proposed in https://www.python.org/dev/peps/pep-0440/
        and http://semver.org/
        
        Testing and application
        =======================
        
        This project provides unittest tests under the tests/ folder. As an example we can see the tracker in action:
        
        .. figure:: https://github.com/davtoh/intelligent-tracker/blob/master/documentation/_static/Scene1_f1.png
            :align: center
            :scale: 5%
        .. figure:: https://github.com/davtoh/intelligent-tracker/blob/master/documentation/_static/Scene1_f2.png
            :align: center
            :scale: 5%
        .. figure:: https://github.com/davtoh/intelligent-tracker/blob/master/documentation/_static/Scene1_f3.png
            :align: center
            :scale: 5%
        .. figure:: https://github.com/davtoh/intelligent-tracker/blob/master/documentation/_static/Scene1_f4.png
            :align: center
            :scale: 5%
        .. figure:: https://github.com/davtoh/intelligent-tracker/blob/master/documentation/_static/Scene1_f5.png
            :align: center
            :scale: 5%
        
        Usage
        =====
        
        Open your console and type ``python main.py``
        
        
        - Contributions and bug reports are appreciated.
        - author: David Toro
        - e-mail: davsamirtor@gmail.com
        - project: https://github.com/davtoh/intelligent-tracker
        
        .. _Licence: https://github.com/davtoh/intelligent-tracker/LICENSE.rst
        .. _Python: http://python.org/
        .. _Sphinx: http://sphinx-doc.org/
        .. _pyinstaller: http://www.pyinstaller.org/
        .. |build-status| image:: https://travis-ci.org/pyserial/pyserial.svg?branch=master
           :target: https://github.com/davtoh/intelligent-tracker/releases
           :alt: Build status
        .. |docs| image:: https://readthedocs.org/projects/pyserial/badge/?version=latest
           :target: http://intelligent-tracker.readthedocs.io/
           :alt: Documentation
        .. _`Unofficial Windows Binaries for Python`: http://www.lfd.uci.edu/~gohlke/pythonlibs/
        .. _`OpenCV linux installation`: https://github.com/davtoh/intelligent-tracker/blob/master/install_opencv.sh
        
        
        
        Intelligent Tracker  |build-status| |docs|
        =========================================================
        
        Overview
        ========
        
        This package provides an API and user interface for tracking objects using haarcascades, keypoints and
        other methods that will be integrated in the future.
        
        The purpose is to create a software to create smart cameras that can detect and follow people
        in a close environment composed of scenes and entries on them like doors or imaginary areas
        where people or objects can be counted or statistics can be obtained.
        
        For now the project is its early stages and the development until the objectives can be reach can take time.
        But for now it offers a demo in the main.py script which hopefully can convey the intend of the project and be useful to someone.
        That said, this code does not intent to compete against commercial software but rather complement them for integration
        with a CCTV system and to not obscure users of what information is being processed from them hence the GPL licence.
        
        Latest:
        
            - Documentation: http://intelligent-tracker.readthedocs.io/
            - Project Homepage: https://github.com/davtoh/intelligent-tracker
        
        Licence:
        
            GPL v3 Licence_
        
        Documentation
        =============
        
        For API documentation, usage and examples see files in the "documentation"
        directory.  The ".rst" files can be read in any text editor or being converted to
        HTML or PDF using Sphinx_. A HTML version will be available soon.
        
        Installation
        ============
        ``pip install intelligent-tracker`` should work for most users.
        
        The usual setup.py for Python_ libraries are used for the source distribution.
        But OpenCV must be installed separately usually compiled from source.
        
        To install OpenCV on windows without much hassle I recommend installing the binaries from
        the `Unofficial Windows Binaries for Python`_ and for Debian distributions I
        provide the bash `OpenCV linux installation`_ so that the user can compile
        openCV (it can take some time). Bear in mind that for Linux it downloads the
        latest 3.x version.
        
        Once successfully installed you can import it in python as:
        
            >>>> import intelligent_tracker as itt
        
        Releases
        ========
        
        All releases follow semantic rules proposed in https://www.python.org/dev/peps/pep-0440/
        and http://semver.org/
        
        Testing and application
        =======================
        
        This project provides unittest tests under the tests/ folder. As an example we can see the tracker in action:
        
        .. figure:: https://github.com/davtoh/intelligent-tracker/blob/master/documentation/_static/Scene1_f1.png
            :align: center
            :scale: 5%
        .. figure:: https://github.com/davtoh/intelligent-tracker/blob/master/documentation/_static/Scene1_f2.png
            :align: center
            :scale: 5%
        .. figure:: https://github.com/davtoh/intelligent-tracker/blob/master/documentation/_static/Scene1_f3.png
            :align: center
            :scale: 5%
        .. figure:: https://github.com/davtoh/intelligent-tracker/blob/master/documentation/_static/Scene1_f4.png
            :align: center
            :scale: 5%
        .. figure:: https://github.com/davtoh/intelligent-tracker/blob/master/documentation/_static/Scene1_f5.png
            :align: center
            :scale: 5%
        
        Usage
        =====
        
        Open your console and type ``python main.py``
        
        
        - Contributions and bug reports are appreciated.
        - author: David Toro
        - e-mail: davsamirtor@gmail.com
        - project: https://github.com/davtoh/intelligent-tracker
        
        .. _Licence: https://github.com/davtoh/intelligent-tracker/LICENSE.rst
        .. _Python: http://python.org/
        .. _Sphinx: http://sphinx-doc.org/
        .. _pyinstaller: http://www.pyinstaller.org/
        .. |build-status| image:: https://travis-ci.org/pyserial/pyserial.svg?branch=master
           :target: https://github.com/davtoh/intelligent-tracker/releases
           :alt: Build status
        .. |docs| image:: https://readthedocs.org/projects/pyserial/badge/?version=latest
           :target: http://intelligent-tracker.readthedocs.io/
           :alt: Documentation
        .. _`Unofficial Windows Binaries for Python`: http://www.lfd.uci.edu/~gohlke/pythonlibs/
        .. _`OpenCV linux installation`: https://github.com/davtoh/intelligent-tracker/blob/master/install_opencv.sh
        
        
        
Keywords: tracker object face color shape recognition scenes visual world
Platform: any
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: End Users/Desktop
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Education
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
