Hi Jordi !

First of all, I would like to thank you for your answer.

Also, I tried your recommandation on OTB 5.6 because with 5.8 I had an 
unexpected error: 
   *Application.logger  (INFO) Number of stream divisions : 4*
*   ERROR 1: No PROJ.4 translation for destination SRS, coordinate 
transformation initialization has failed.*
*   /usr/bin/otbcli: line 37: 30426 Segmentation fault     
 $OTB_CLI_LAUNCHER "$@*"

Anyway, I used two different algorithms : SVM and KNN.
For SVM I had this message: "*(WARNING) Confidence map requested but the 
classifier doesn't support it!*"
In your mail, you wrote me that I need  a model with probability estimates, 
so is the issue coming from here? Or is it due to the fact that I'm in 5.6?

For KNN, I have an other kind of problem: 
  * Application.logger  (FATAL) The following error occurred during 
application execution : 
/home/mrashad/dashboard/otb/src/Modules/IO/ImageIO/include/otbImageFileWriter.txx:443:*
*   Could not create IO object for file uint16*
*   Tried to create one of the following:*
*      RADImageIO*
*      BSQImageIO*
*      LUMImageIO*
*      TileMapImageIO*
*      GDALImageIO*
*      MWImageIO*
*      ONERAImageIO*
*      MSTARImageIO*
*    You probably failed to set a file suffix, or set the suffix to an 
unsupported type.*

I've checked my script but it seems good to me...
So, do you know how I can resolve my problems ?

Thanks in advance, 
CK





Le mardi 14 février 2017 17:22:37 UTC+1, Jordi Inglada a écrit :
>
> Hi, 
>
> The -io.confmap option does not exist in the TrainImagesClassifier 
> application. There is an -io.confmatout option to compute the confusion 
> matrix. 
>
> However, the ImageClassifier application has the -confmap option which 
> generates what you want: a raster image with the confidence estimated for 
> each pixel in the classification. The confidence is estimated in a 
> different way depending on the classification algorithm. From the 
> documentation: 
>
>       "  - LibSVM : difference between the two highest probabilities 
> (needs a model with probability estimates, so that classes probabilities 
> can be computed for each sample)\n" 
>       "  - OpenCV\n" 
>       "    * Boost : sum of votes\n" 
>       "    * DecisionTree : (not supported)\n" 
>       "    * GradientBoostedTree : (not supported)\n" 
>       "    * KNearestNeighbors : number of neighbors with the same 
> label\n" 
>       "    * NeuralNetwork : difference between the two highest 
> responses\n" 
>       "    * NormalBayes : (not supported)\n" 
>       "    * RandomForest : Confidence (proportion of votes for the 
> majority class). Margin (normalized difference of the votes of the 2 
> majority classes) is not available for now.\n" 
>
> Jordi 
>
> CK <[email protected] <javascript:>> wrote: 
> > 
> > Hi everyone ! 
> > 
> > I'm new on OTB (5.6 & 5.8) and I have some questions about the 
> possibility to get the probability of belonging of a pixel to a class 
> (after or during a classification). 
> > 
> > I tried to use the -io.confmap "option" of the 
> otbcli_TrainImagesClassifier tools but I only get a matrix on my samples. 
> > In fact, I would like to obtain a raster on my entire aoi with a value 
> (between 0 and 1) for each pixel. 
> > 
> > I also saw in a previous post on the group the possibility to call the 
> EvaluateProbabilities. 
> > I'm not very familiar with this so do you know if there is any other way 
> to have my probability raster for my classification (using a pre-existing 
> tools may be) ? 
> > 
> > Thanks in advance for your help ! 
> > C. 
> > 
> > -- 
>

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