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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