software

A quick request out to tintii users on flickr — any photos that you’ve put up where you’ve used tintii somewhere in the process of preparation, please tag with "tintii". What I’d like to do is get a group together soon to collect these examples together into one place. There’s a certain critical mass needed for such a group to be successful, so we’ll just start with this simple tagging scheme for now to see if there are enough of us out there.

Please drop me an email to let me know if you have tintii photos up on other websites, or even just send your work to me, it’s always great to see!

Version 2 of Tint Photo Editor, redubbed tintii, has now been released. This version marks a major upgrade to the software, most particularly with the inclusion of a Photoshop plug-in.

tintii is a smart photo filter for striking colour select effects. Also known as colour popping, think Schindler’s List’s little girl in red, or the dramatic style of Sin City. The new release includes:

• An overhauled interface, quicker and more intuitive to use.
• A Photoshop plug-in to unleash the power of tintii in conjunction with Adobe’s juggernaut image editing suite.
• Orders of magnitude improved performance that now facilitates real-time editing.
• New post-processing tools to give finer control over the filter effect, and particularly handle whispy hair and other difficult edging tasks.

The standalone version of tintii remains free, open source software available on both Linux and Windows. The Photoshop plug-in, available only on Windows, requires the purchase of a registration key in order to activate. To retail at a regular price of AU$29, for a limited time it will be on offer at AU$14 (approximately US$9, GB£7 or EU€7) to mark its first release.

Two example applications have been made available for dysii, a toy linear model and more elaborate double well stochastic differential model. The former of these will serve as a useful tutorial example for those wanting to learn to use the library. The latter is a more complex application with a number of features that make it ideal as a template for more serious work.

Version 1.4.0 of the dysii Dynamic Systems Library has been released. This is a major new release with a number of additional features and performance enhancements, as well as representing a consolidation of code and maturation of much of the API.

Particular new features include:

• The kernel forward-backward and two-filter smoothers, suitable for fast, large-scale approximate inference in continuous-time stochastic models, as documented in my recent PhD thesis.
• Overhauled kd tree implementation, featuring distributed partitioning, dual-tree and self-tree evaluations, particularly useful for the new smoothers above.
• Improved stochastic Runge-Kutta and new Euler-Maruyama method for integrating stochastic differential equations.
• Performance improvements resulting from continued profiling, including more aggressive inlining and less dependence on virtuals.
• A new installation guide, available in the INSTALL.txt file of the distribution. Also note that with Boost 1.35 now released, dysii no longer requires the latest CVS of Boost, making it much simpler to install.

Full details are included in the VERSION.txt file of the distribution.

A couple of examples of applications using dysii are expected to be released within a matter of days also. These should provide an excellent starting point for those wishing to use the library for their own work.