It is only for libsvm train vector classifier. When the option parameters
optimization is enabled, the trainer tries to optimize but without stopping
(the process is performed again, and again like a loop without ending with
the confusion matrix), whatever the kernel used (same issue for rbf,
polynomial, sigmoid and linear). I don't know which new code has been
written since 6.6.0 and that could explain this bug. I have also noticed
that this issue appears on both windows and linux systems.



Le sam. 10 nov. 2018 21:11, Katie Sanders <[email protected]> a
écrit :

> Thank you! The train vector classifier tool completed fine with the
> parameters optimization enabled, is it the trainer or the train vector
> classifier that has a bug or the vector classifier where the bug happens?
>
> On Thursday, November 8, 2018 at 2:58:39 PM UTC-6, Etienne MAHE wrote:
>>
>> Hi,
>>
>> Yes, if you previousely use the module Compute Image Order second
>> statistics to generate an xml file, the number of features must match to
>> the number of bands of the image used for the classifications. From my
>> experience for classification of aerial photos (rgb and nir), only mean and
>> medians seem revelant. As for example, with six bands, you can use up to
>> six features.
>> And just to let you know, the libsvm classifier seems to have issues with
>> the last otb version when you enable parameters optimization. Awaiting a
>> bug fix, I use the 6.4.0 which works fine. You should find this version on
>> OTB repository.
>>
>> Sincerely,
>> Etienne.
>>
>> Le jeu. 8 nov. 2018 21:40, Katie Sanders <[email protected]> a écrit :
>>
>>> I am doing an object based classification. I have completed the 4 steps
>>> of the Large Scale Mean Shift Segmentation in OTB. I am trying to use the
>>> TrainVectorClassifier tool but am getting an error regarding the Field
>>> names for training features. The training shapefile has means and variances
>>> of 18 bands that I am trying to use as training features. I am using OTB
>>> 6.6 with QGIS 3. Here is the log of the application.
>>>
>>> C:\WINDOWS\system32>SET LC_NUMERIC=C
>>>
>>>
>>> C:\WINDOWS\system32>SET GDAL_DRIVER_PATH=disable
>>>
>>>
>>> C:\WINDOWS\system32>SET "GDAL_DATA=C:\OTB-6.6.0-Win64\share\data"
>>>
>>>
>>> C:\WINDOWS\system32>SET "GEOTIFF_CSV=C:\OTB-6.6.0-Win64\share\epsg_csv"
>>>
>>>
>>> C:\WINDOWS\system32>SET
>>> "OTB_APPLICATION_PATH=C:\OTB-6.6.0-Win64\lib\otb\applications"
>>>
>>>
>>> C:\WINDOWS\system32>"C:\OTB-6.6.0-Win64\bin\otbApplicationLauncherCommandLine.exe"
>>> TrainVectorClassifier C:/OTB-6.6.0-Win64/lib/otb/applications -cfield
>>> "class" -classifier "libsvm" -classifier.libsvm.c "100000.0"
>>> -classifier.libsvm.k "rbf" -classifier.libsvm.m "oneclass" -
>>> classifier.libsvm.nu "0.001" -feat "meanB0" "meanB1" "meanB2" "meanB3"
>>> "meanB4" "meanB5" "meanB6" "meanB7" "meanB8" "meanB9" "meanB10" "meanB11"
>>> "meanB12" "meanB13" "meanB14" "meanB15" "meanB16" "meanB17" "varB0" "varB1"
>>> "varB2" "varB3" "varB4" "varB5" "varB6" "varB7" "varB8" "varB9" "varB10"
>>> "varB11" "varB12" "varB13" "varB14" "varB15" "varB16" "varB17"
>>> -io.confmatout "B:/Masters Project/Wowetta/Classification/Confusion
>>> Matrix/svmmatrix1.csv" -io.out "B:/Masters
>>> Project/Wowetta/Classification/Model/svmmodel1.txt" -io.stats "B:/Masters
>>> Project/Wowetta/Classification/p_imagestatistics.xml" -io.vd "B:\Masters
>>> Project\Wowetta\Classification\Training\w_tile2_1_training.shp" "B:\Masters
>>> Project\Wowetta\Classification\Training\w_tile2_2_training.shp" -v "True"
>>> -valid.vd "B:\Masters
>>> Project\Wowetta\Classification\Training\w_Tile1_1training.shp" "B:\Masters
>>> Project\Wowetta\Classification\Training\w_tile3_1_training.shp" "B:\Masters
>>> Project\Wowetta\Classification\Training\w_tile3_2_training.shp"
>>>
>>> 2018-11-08 13:49:24 (INFO): Default RAM limit for OTB is 128 MB
>>>
>>> 2018-11-08 13:49:24 (INFO): GDAL maximum cache size is 1634 MB
>>>
>>> 2018-11-08 13:49:24 (INFO): OTB will use at most 8 threads
>>>
>>> 2018-11-08 13:49:24 (INFO): Reading vector file 1/2
>>>
>>> 2018-11-08 13:49:24 (INFO): Reading vector file 2/2
>>>
>>> 2018-11-08 13:49:24 (FATAL): itk::ERROR:
>>> ShiftScaleSampleListFilter(00000239450C43A0): Inconsistent measurement
>>> vector size : Input Sample List size 36 Scale measurement vector size 18
>>> Shift measurement vector size 18
>>>
>>>
>>> Can Anyone help me with this error and how to remedy it? I understand I
>>> have 18 mean features and 18 variance features. Which together is the
>>> sample list of 36. Am I only able to use 18 of the features?
>>>
>>>
>>> Katie
>>>
>>> --
>>> --
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>>> http://www.orfeo-toolbox.org/FAQ.html
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>> --
> --
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> http://www.orfeo-toolbox.org/FAQ.html
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