Just to finish, there is no issue, neither with other train vector
classifier (such as random forest or knn), nor with vector classifier.

Le sam. 10 nov. 2018 21:21, Etienne MAHE <yitiane...@gmail.com> a écrit :

> 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 <sanders.kat...@gmail.com> 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 <sanders...@gmail.com> 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
>>>>
>>>> --
>>>> --
>>>> Check the OTB FAQ at
>>>> http://www.orfeo-toolbox.org/FAQ.html
>>>>
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>>>>
>>> --
>> --
>> Check the OTB FAQ at
>> http://www.orfeo-toolbox.org/FAQ.html
>>
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