Implements the CAM02-UCS forward transform symbolically, using Theano.
Project description
Implements the CAM02-UCS (Luo et al. (2006), “Uniform Colour Spaces Based on CIECAM02 Colour Appearance Model”) forward transform symbolically, using Theano.
See: CIECAM02 and Its Recent Developments.
The forward transform is symbolically differentiable in Theano and it may be approximately inverted, subject to gamut boundaries, by constrained function minimization (e.g. projected gradient descent or L-BFGS-B).
Package contents
constants.py contains constants needed by CAM02-UCS and others which are merely useful.
functions.py contains compiled Theano functions, as well as NumPy equivalents of other symbolic functions.
symbolic.py implements the forward transform symbolically in Theano. The functions therein can be used to construct custom auto-differentiable loss functions to be subject to optimization.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.