[ITK] [ITK-users] ITK Python: numpy to itk image (and viceversa)

Wed Apr 12 16:26:06 EDT 2017

I reproduced the error. I am looking into fixing it.

On Wed, Apr 12, 2017 at 4:02 PM, D'Isidoro Fabio <fisidoro at ethz.ch> wrote:

> Ok, thanks. Moe specifically I am using now *Visual Studio 2017 Preview*.
>
>
>
> Fabio.
>
> *From:* Dženan Zukić [mailto:dzenanz at gmail.com]
> *Sent:* Mittwoch, 12. April 2017 21:54
> *To:* D'Isidoro Fabio <fisidoro at ethz.ch>
> *Cc:* Matt McCormick <matt.mccormick at kitware.com>; insight-users at itk.org
>
> *Subject:* Re: [ITK-users] ITK Python: numpy to itk image (and viceversa)
>
>
>
> Hi Fabio,
>
>
>
> let me give it a try with VS2017 and Wrapping+NumPy. I will report back
> when I have an update.
>
>
>
> Regards,
>
> Dženan Zukić, PhD, Senior R&D Engineer, Kitware (Carrboro, N.C.)
>
>
>
> On Wed, Apr 12, 2017 at 2:16 PM, D'Isidoro Fabio <fisidoro at ethz.ch> wrote:
>
> Thank you. I am trying to build ITK Wrap Python with Module_BridgeNumPy=ON
> with Visual Studio 2017.
>
> I get the following type of errors:
>
> 12>C:/Program Files (x86)/Microsoft Visual Studio/Preview/Community/VC/
> Tools/MSVC/14.10.25017/include\xstring(1905,26): error G3F63BFAE:
> constexpr variable '_Memcpy_move_offset' must be initialized by a constant
> expression
> 12>        static constexpr size_t _Memcpy_move_offset =
> offsetof(_Mydata_t, _Bx);
> 12>                                ^
>  ~~~~~~~~~~~~~~~~~~~~~~~~
> 12>C:/Program Files (x86)/Microsoft Visual Studio/Preview/Community/VC/
> Tools/MSVC/14.10.25017/include\stdexcept:23:21: note: in instantiation of
> template class 'std::basic_string<char, std::char_traits<char>,
> std::allocator<char> >' requested here
> 12>                : _Mybase(_Message.c_str())
> 12>                                  ^
> 12>C:/Program Files (x86)/Microsoft Visual Studio/Preview/Community/VC/
> Tools/MSVC/14.10.25017/include\xstring:1905:48: note: cast that performs
> the conversions of a reinterpret_cast is not allowed in a constant
> expression
> 12>        static constexpr size_t _Memcpy_move_offset =
> offsetof(_Mydata_t, _Bx);
> 12>                                                      ^
> 12>C:/Program Files (x86)/Windows Kits/10/Include/10.0.10586.0/ucrt\stddef.h:38:32:
> note: expanded from macro 'offsetof'
> 12>        #define offsetof(s,m) ((size_t)&reinterpret_cast<char const
> volatile&>((((s*)0)->m)))
>
>
> The build worked with Visual Studio 2015 instead.
>
> Can I fix this issue with Visual Studio 2017 somehow?
>
> Thank you.
>
> ----------------------------------------------------------------------
> Fabio D’Isidoro - PhD Student
> Institute of Biomechanics
> HPP O 14
> Hönggerbergring 64
> 8093 Zürich, Switzerland
>
>
> -----Original Message-----
> From: Matt McCormick [mailto:matt.mccormick at kitware.com]
> Sent: Montag, 3. April 2017 20:41
> To: D'Isidoro Fabio <fisidoro at ethz.ch>
> Cc: insight-users at itk.org
> Subject: Re: [ITK-users] ITK Python: numpy to itk image (and viceversa)
>
> Hallo Fabio,
>
>
> > I use ITK with Python Wrap. I need to interface my Python code with a
> > Cython-wrapped C++ code that takes only numpy array as input and
> > returns numpy array as output.
>
> Cool. By the way, you may be interested in scikit-build [1], which is a
> good way to build Cython-wrapped C++ code. We are using it for the ITK and
> SimpleITK Python packages, and it has good Cython and CMake support.
>
>
> > Hence, I need to convert the Python itk images into numpy array to be
> > given as input to the wrapped C++ code, and then convert the numpy
> > array in output from the wrapped C++ code back into python itk images.
> >
> >
> >
> > Question 1) How can I do that in an efficient way? I found some posts
> > on itk.PyBuffer but I could not find anywhere any reference on how to
> > install it on my itk wrap build.
>
> Yes, itk.PyBuffer works great for that. Please review a PR for some
> additional documentation:
>
>   https://github.com/InsightSoftwareConsortium/ITKBridgeNumPy/pull/18
>
> This has been available in ITK for a few releases as a Remote module,
> which can be enabled by setting
>
>   Module_BridgeNumPy=ON
>
> in ITK's CMake configuration.
>
>
> Since ITK 4.11.0, it is easier to build since it does not require the
> NumPy headers.
>
>
> In current ITK Git master (to be 4.12.0) the module is enabled by default.
>
>
> Nightly ITK Python packages for ITK Git master are now being built:
>
>   https://github.com/InsightSoftwareConsortium/ITKPythonPackage
>
> macOS and Linux are available. Windows packages will be available over the
> coming weeks.
>
>
>
> > Question 2) The purpose of writing a part of my algorithm in C++ is to
> > speed up the code. If the conversion between python itk images and
> > numpy arrays is slow, I would lose all the speed gain obtained with the
> C++ implementation.
> > Are there better ways to deal with that?
>
> The newer versions ITKBridgeNumPy use a NumPy array view, which does not
> do any copies during the conversion, and it is very fast.
>
>
> HTH,
> Matt
>
>
> [1] http://scikit-build.org/
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