My mistake, it is the compute image second order statistics.

Le jeu. 8 nov. 2018 21:58, Etienne MAHE <[email protected]> a écrit :

> 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
>>
>> --
>> --
>> Check the OTB FAQ at
>> http://www.orfeo-toolbox.org/FAQ.html
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>

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