Using swig on external standalone libraries that use ITK

Hello Insight-Users,
I’ve studied the WrapITK CMake modules and an old wiki describing how to wrap external modules, but I’ve yet to see anything obvious about wrapping a standalone library that uses ITK. Since ITK is a toolkit used to build other applications and libraries, wrapping your library with swig and using it in concert with WrapITK seems pretty natural to me.

Swig can wrap the library that uses ITK. But the Python types for the ITK data structures do not match those from the WrapITK Python module.

I don’t have any actual examples handy, but here’s roughly what will generally happen:
x = MyModule.vectorI2()
x.resize(1)
type(x[0])
itk::Index< 2 >

y = itk.Index2
type(y)
itkIndexPython.itkIndex2

x.push_back(y)
Type mismatch error happens (itk::Index< 2 > const & expected)

I also see that WrapITK generates a lot of new types/typedefs for every class in its Wrapping build folder. For example, I’m sure I’ll never be able to use itk::Image<unsigned char, 2>::Pointer with itk.Image[itk.UC, 2]. The latter is comprised of 2 brand new standalone classes defined in itkImageSwigInterface.h… itkImageUC2 and itkImageUC2_Pointer. Swig’s typedef reduction will never be able to match itk::Image<T,D>::Pointer with those wrapped types even if I import the respective itkImage headers/interfaces. Heck, it can’t even match the typedefs from itkIndexSwigInterface.h as it is. If I import the itkIndex.i or itkIndexSwigInterface.h and instantiate

%template(vectorI2) std::vector;

mysteriously it still reduces to itk::Index< 2 >.

Is there anyway I can convince swig that the data types provided by the itk module are the same data types I’m using in MyModule without having to turn it into an ITK module outright?

Hi, any update on this approach of wrapping itk with an external module using swig ?

Thanks

GT

A question for @matt.mccormick?

We have very good support for wrapping external standalone libraries with swig. Cross-platform and cross-Python version packages will be built by GitHub CI and automatically uploaded to the Python Package Index (PyPI) when a tag is created on GitHub. To quickly get started, see:

There are many examples in the InsightSoftwareConsortium GitHub Organization: