Posts Tagged ‘PyDIP’

Presenting DIPlib 3.0

Sunday, August 20th, 2017

DIPimage is a MATLAB toolbox for quantitative image analysis. We’ve got quite a few users, especially in academia. However, few of those users (as far as I know) have ventured down the path of directly using DIPlib, the C library that DIPimage is built upon. I know of two people, outside of the group at Delft University of Technology where we developed DIPlib and DIPimage, that have written C code that uses DIPlib. And that is too bad, because it’s a wonderful library. There are two reasons for this lack of uptake: it has a very steep learning curve, and it is not open source. The second reason makes the first one worse, because there’s very little example source code to look at for learning to use the library.

Back in 2014 I started dreaming of porting DIPlib to C++, and making it open source. Modern C++ is a very expressive language, and writing code that uses a C++ version of DIPlib doesn’t need to be much more complicated that writing the equivalent MATLAB code. The port would allow moving some of the innovations we introduced in DIPimage into the DIPlib library, such as tensor (vector or matrix) images, color space management, etc. I did write a first version of the dip::Image class to test and learn how the library could look, and write proposals trying to convince people to help me build it, but otherwise didn’t put much effort into the project until last year. Over the last year and a half or so, I have invested a lot of my free time to build a whole new library infrastructure, and port over algorithms. The work is not nearly finished, but there already is a lot there, and I have been using it at work in production code. Even though I initially set out to port algorithms unmodified, I find myself improving code quite frequently, some algorithms are significantly faster than they were before (e.g. the Watershed, which now uses a correct implementation of Union-Find, and the labelling algorithm (connected component analysis), which now uses a completely different algorithm).

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