<commit_before>[![Build Status](https://travis-ci.org/mjirik/larVolumeToObj.svg?branch=master)](https://travis-ci.org/mjirik/larVolumeToObj)

lar-running-demo
=============

A demo beta software (set of scripts) to extract models from medical images.
First step is image segmentation by Lisa software.

Spftware has been tested on Ubuntu 14.04 LTS (x64).

MIT License.


Install
======

Install PyPlasm

Download LAR somewhere in your home directory. It will be found automatically.

    sudo apt-get install python-scipy python-numpy python-matplotlib\
        python-dicom cython python-pip

    pip install larVolumeToObj
    

Sample data
===========

https://github.com/mjirik/lar-running-demo/blob/master/tests/nrn4.pklz


Library
=======

    import larVolumeToObj.computation as larobj
    larobj.pklzToSmoothObj.makeSmooth('nrn4.pklz', visualization=True)

More exaples
------------

    V, F = larobj.pklzToSmoothObj.makeSmooth('nrn4.pklz')
    larobj.visualization.visualize(V, F, explode=True)
    larobj.visualization.visualizeObj('output/out_sm_i_tr.obj', explode=True)



Commandline tools<commit_msg>fix bad data url<commit_after>[![Build Status](https://travis-ci.org/mjirik/larVolumeToObj.svg?branch=master)](https://travis-ci.org/mjirik/larVolumeToObj)

lar-running-demo
=============

A demo beta software (set of scripts) to extract models from medical images.
First step is image segmentation by Lisa software.

Spftware has been tested on Ubuntu 14.04 LTS (x64).

MIT License.


Install
======

Install PyPlasm

Download LAR somewhere in your home directory. It will be found automatically.

    sudo apt-get install python-scipy python-numpy python-matplotlib\
        python-dicom cython python-pip

    pip install larVolumeToObj
    

Sample data
===========

https://github.com/mjirik/larVolumeToObj/blob/master/tests/nrn4.pklz?raw=true


Library
=======

    import larVolumeToObj.computation as larobj
    larobj.pklzToSmoothObj.makeSmooth('nrn4.pklz', visualization=True)

More exaples
------------

    V, F = larobj.pklzToSmoothObj.makeSmooth('nrn4.pklz')
    larobj.visualization.visualize(V, F, explode=True)
    larobj.visualization.visualizeObj('output/out_sm_i_tr.obj', explode=True)



Commandline tools
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{'dir': 'git-commits-cleaned', 'id': '6356320', 'n_tokens_mistral': 813, 'n_tokens_neox': 728, 'n_words': 170}