Little CMS 2.12 released I am glad to the announce the release 2.12 of the LittleCMS open source color engine. lcms2-2.12 will add stability. Most of the new development has been done in fast float plug-in, now we have a integrated build system (a command line option in configure script) and more kernels, RGB to anything, and Lab to anything. The path “Lab to RGB” in float is specially useful. This release also recovers PDF for documentation, but at a reduced size.
I’ve been using Qt, by Qt Group for years and I must confess I am delighted. Many toolkits promises the mantra “Code once and run everywhere”, but indeed this works with Qt. Qt6 was announced few days ago. They now include some sort of color management on images QColorSpace, but still no neat way to use complex ICC V4 pipelines. In this small article I will show you how to do true RGB color management in Qt, by using LittleCMS, with very few lines of code.
From time to time, I discover wonderful things like this: GIMP 2.10 release notes “GIMP now uses LittleCMS v2, which allows it to use ICC v4 color profiles. It also partially relies on the babl library for handling color transforms, since babl is simply up to 10 times faster than LCMS2 for the cases we tested both of them on. Eventually babl could replace LittleCMS in GIMP.” OMG! something seems very wrong with the Little CMS engine!
After a long period of inactivity, I am happy to announce the release of lcms2-2.11. It includes bug fixes and some compilation aids, like the possibility of removing the “register” modifier. MD5 is now accesible in API. PostScript CSA generation is also much better, solving historical performance issues on PostScript which affect many intepreters, Camelot, Ghostscript… Maybe the biggest difference of 2.11 with other releases lies in the bundle with the “fast float” plug-in.
Days ago, a very interesting question arose in the mailing list. How can I visualiza the gamut of a profile? Little CMS does not offer direct tools to do that. But with some code, it is easy to do so. Be warned there is some hacking required. A typical profile can be thought as a “black box” that translates values from a colorimetric space, usually CIE L*a*b*, to a device space.