Hi Jonathan,

Yes, that's it ! Sometimes, I'm scatterbrained.
Thank you very much !

Sylvio


Le mardi 21 janvier 2014 11:32:11 UTC+1, Jonathan Guinet a écrit :
>
> Hi, 
>
> below the test command example given from command line application :
>
>
>
>
> *Examples: otbcli_TrainImagesClassifier -io.il <http://io.il> 
> QB_1_ortho.tif -io.vd VectorData_QB1.shp -io.imstat 
> EstimateImageStatisticsQB1.xml -sample.mv <http://sample.mv> 100 -sample.mt 
> <http://sample.mt> 100 -sample.vtr 0.5 -sample.edg false -sample.vfn Class 
> -classifier libsvm -classifier.libsvm.k linear -classifier.libsvm.c 1 
> -classifier.libsvm.opt false -io.out svmModelQB1.txt -io.confmatout 
> svmConfusionMatrixQB1.csv *
> -io.confmatout  refers to confusion matirx output
> -io.out to the SVM model generated 
>
> you should try to invert those two ouput
>
> Jonathan
>
>
>
> 2014/1/21 Sylvio L. <[email protected] <javascript:>>
>
>> Dear all, 
>>
>> I working on OTB in QGIS. I try to classify an image with the module 
>> TrainImagesClassifier (svm). 
>>
>> First, I calculated image's statistics with "ComputeImagesStatistics". 
>> Then I used this results in the module TrainImagesClassifier as this 
>> (without error): 
>>
>> otbcli_TrainImagesClassifier -io.il 11_Variance_S2.tif -io.vd 
>> 4ClassifSVM.shp -io.imstat XML11.xml 
>>  -sample.mt -1 -sample.mv -1 -sample.vtr 0.5 -sample.vfn SVM -classifier 
>> svm 
>>  -classifier.svm.m csvc -classifier.svm.k linear -classifier.svm.c 1 
>> -classifier.svm.opt true 
>>  -io.confmatout SVMMODELQB2.SVM -io.out SVMCONFUSIONMATRIXQB2.csv 
>>
>> And finally, I launched the process to extract my image's classification 
>> : 
>> otbcli_ImageClassifier -in 11_Variance_S2.tif -model SVMMODELQB2.SVM 
>> -imstat XML11.xml 
>>  -ram 128 -out SVM_S2_11_.tif 
>>
>> At the last step I get an error : 
>> Application.logger  (FATAL) Error when loading model SVMMODELQB2.SVM : 
>> unsupported model type 
>>
>> Yet, this is a file from OTB's module. I don't understand . 
>> In the file *.svm : 
>> --------------------------------------- 
>> #Reference labels (rows):1,2,3 
>> #Produced labels (columns):1,2,3 
>> 36,0,1359401 
>> 0,0,1359042 
>> 81,0,1358023 
>> --------------------------------------- 
>>
>> Could you help me, please ?! 
>> Thank you in advance, for your answers !
>>
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>

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