Difference between revisions of "Summer2009:Using ITK in python"

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<h3>Objective</h3>
 
<h3>Objective</h3>
Develop strategies for embedding ITK filters in python code.
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Develop strategies for embedding ITK filters in python code.  See if this would be a workable strategy for creating slicer modules.
  
 
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<h3>Progress</h3>
 
<h3>Progress</h3>
 
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* Some pre-project week progress is shown [https://www.slicer.org/wiki/Slicer3:Python:pitky on this page in the slicer.org wiki]
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* Debugging of python internals with Demian and discussion of future directions.
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* Basic possibilities (all are somewhat convoluted):
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** WrapITK - combinatorial explosion; large libraries; C++ no longer available
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** Cython - yet another language; not clear how to use C++ idioms
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** Ctypeslib - good for teem.py, not good for C++
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** Weave - clear access to C++; can pass numpy arrays
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** Invoke CLI - clear distinction of C++ and python; easily supports multiple calling languages; CLIs are reusable executables/libraries; clear how to deploy; ITK IO requires one memcopy; approach is pretty indirect.
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* Confirmation that weave is a promising approach, but CLI still seems to be preferred approach.
  
 
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==References==
  
==References==
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* http://www.slideshare.net/gsroma/integrando-c-com-python-presentation (in portugese)
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* http://www.scipy.org/Cookbook/Weave

Latest revision as of 17:39, 10 July 2017

Home < Summer2009:Using ITK in python


Key Investigators

  • GE: Jim Miller
  • Isomics: Steve Pieper
  • INRIA: Demian Wassermann

Objective

Develop strategies for embedding ITK filters in python code. See if this would be a workable strategy for creating slicer modules.

Approach, Plan

  • Look at how numpy arrays are passed to C/C++ code using techniques like cython, weave, etc.
  • Figure out what is needed to compile ITK code in these environments.
  • Compare and contrast this approach to WrapITK

Progress

  • Some pre-project week progress is shown on this page in the slicer.org wiki
  • Debugging of python internals with Demian and discussion of future directions.
  • Basic possibilities (all are somewhat convoluted):
    • WrapITK - combinatorial explosion; large libraries; C++ no longer available
    • Cython - yet another language; not clear how to use C++ idioms
    • Ctypeslib - good for teem.py, not good for C++
    • Weave - clear access to C++; can pass numpy arrays
    • Invoke CLI - clear distinction of C++ and python; easily supports multiple calling languages; CLIs are reusable executables/libraries; clear how to deploy; ITK IO requires one memcopy; approach is pretty indirect.
  • Confirmation that weave is a promising approach, but CLI still seems to be preferred approach.

References