Metadata-Version: 1.1
Name: colorspacious
Version: 1.1.0
Summary: A powerful, accurate, and easy-to-use Python library for doing colorspace conversions
Home-page: https://github.com/njsmith/colorspacious
Author: Nathaniel J. Smith
Author-email: njs@pobox.com
License: MIT
Description: colorspacious
        =============
        
        .. image:: https://travis-ci.org/njsmith/colorspacious.svg?branch=master
           :target: https://travis-ci.org/njsmith/colorspacious
           :alt: Automated test status
        
        .. image:: https://codecov.io/gh/njsmith/colorspacious/branch/master/graph/badge.svg
           :target: https://codecov.io/gh/njsmith/colorspacious
           :alt: Test coverage
        
        .. image:: https://readthedocs.org/projects/colorspacious/badge/?version=latest
           :target: http://colorspacious.readthedocs.io/en/latest/?badge=latest
           :alt: Documentation Status
        
        Colorspacious is a powerful, accurate, and easy-to-use library for
        performing colorspace conversions.
        
        In addition to the most common standard colorspaces (sRGB, XYZ, xyY,
        CIELab, CIELCh), we also include: color vision deficiency ("color
        blindness") simulations using the approach of Machado et al (2009); a
        complete implementation of `CIECAM02
        <https://en.wikipedia.org/wiki/CIECAM02>`_; and the perceptually
        uniform CAM02-UCS / CAM02-LCD / CAM02-SCD spaces proposed by Luo et al
        (2006).
        
        To get started, simply write::
        
          from colorspacious import cspace_convert
        
          Jp, ap, bp = cspace_convert([64, 128, 255], "sRGB255", "CAM02-UCS")
        
        This converts an sRGB value (represented as integers between 0-255) to
        CAM02-UCS `J'a'b'` coordinates (assuming standard sRGB viewing
        conditions by default). This requires passing through 4 intermediate
        colorspaces; ``cspace_convert`` automatically finds the optimal route
        and applies all conversions in sequence:
        
        This function also of course accepts arbitrary NumPy arrays, so
        converting a whole image is just as easy as converting a single value.
        
        Documentation:
          http://colorspacious.readthedocs.org/
        
        Installation:
          ``pip install colorspacious``
        
        Downloads:
          https://pypi.python.org/pypi/colorspacious/
        
        Code and bug tracker:
          https://github.com/njsmith/colorspacious
        
        Contact:
          Nathaniel J. Smith <njs@pobox.com>
        
        Dependencies:
          * Python 2.6+, or 3.3+
          * NumPy
        
        Developer dependencies (only needed for hacking on source):
          * nose: needed to run tests
        
        License:
          MIT, see LICENSE.txt for details.
        
        References for algorithms we implement:
          * Luo, M. R., Cui, G., & Li, C. (2006). Uniform colour spaces based on
            CIECAM02 colour appearance model. Color Research & Application, 31(4),
            320–330. doi:10.1002/col.20227
          * Machado, G. M., Oliveira, M. M., & Fernandes, L. A. (2009). A
            physiologically-based model for simulation of color vision
            deficiency. Visualization and Computer Graphics, IEEE Transactions on,
            15(6), 1291–1298. http://www.inf.ufrgs.br/~oliveira/pubs_files/CVD_Simulation/CVD_Simulation.html
        
        Other Python packages with similar functionality that you might want
        to check out as well or instead:
        
        * ``colour``: http://colour-science.org/
        * ``colormath``: http://python-colormath.readthedocs.org/
        * ``ciecam02``: https://pypi.python.org/pypi/ciecam02/
        * ``ColorPy``: http://markkness.net/colorpy/ColorPy.html
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
