TubeTK/Design Discussions: Difference between revisions

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= Introduction =
Tubetk has adopted [ MIDAS] to store testing and algorithm validation dataset. For this purpose, we have created a dedicated [ tubetk MIDAS community]

In the tubetk community, we have two main types of folders
#'''Input data folder''': Where all input data for testing will be stored
#'''Baseline dataset folder''': These are individual folders that will be used to store the baseline images for regression tests in tubetk
= How to add a new tubetk test =
#If the input data is not already in Midas,
##Upload the data to the "Data" folder
##Download the key file (*.md5) and store it in the MIDAS_KEYS directory at the top level of tubetk source code tree
#Add baseline dataset for the new test ( if your test is a regression testing )
##Upload the dataset to the appropriate CLI or module folder. If your test is part of a new "module" or CLI, create a new a folder in MIDAS and then upload the dataset
##Download the key file  (*.md5) for the baseline image and store it in the MIDAS_KEYS directory.
#Modify cmake list files in the Testing directory to "add" unit tests to use the data from MIDAS.
##Use MIDAS_FETCH_ONLY macro, if you would like to fetch the dataset but not use it directly in the test
##Use MIDAS_DIRECTORY, if you would like to specify a whole directory as an input command line argument to your test
Test using a data store in MIDAS
            ${TEMP}/SyntheticTubePlusSurfaceEEDFilterResultImage_oriented.mha )
Test with a directory as input argument: DICOMSeries
              -a Test1 001
              -o ${TEMP}
              -b DSC_
              MIDAS_DIRECTORY{DICOMSeries} )
Test that demonstrates fetch only option: tubeEdgeEnhancingAnisotropicDiffusionMIDAS-Test1
= MIDAS macro =
The following are the essential midas macros for setting up a test using data stored in midas.

Latest revision as of 18:40, 26 July 2013