Overview¶
Colorspacious
is a powerful, accurate, and easy-to-use Python
library for performing colorspace conversions.
- Documentation:
- https://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:
- 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