Hi,

the application "by default" split each polygon in 2 to select training and
validation samples. There are in the application some parameters which
allow to control (partialy) the way that this sample is done
(training/validation samples ratio, max number of samples...)

Long story short there are now in last OTB version (5.6) new applications
which allows to have a far better control on the way you're selecting
pixels as samples in polygons.

Look at the applications: PolygonClassStatistics (outputs statistics about
the sample distribution in the input polygons), SampleExtraction (extract
samples from polygons (all, regularly, randomly...) and then
TrainVectorClassifier (train a classifier with as input for the learning
the output from SampleExtraction).

There is not yet a complete recipe in the CookBook about the sampling
strategy and possible options (the reference documentation of all these
applications are there however) but it should help you to create a workflow
with existing OTB app which allows to control samples on which your
learning the classification model.

With the learning model you can then apply the classification with
ImageClassifier app (same as in the pixel based image classification recipe
in the cookbook).

Don't hesitate if you've got any feedback.

Regards,

2016-08-30 16:08 GMT+02:00 GeoFan <johw...@gmail.com>:

> Hello everyone,
>
> I want to know if the tool "TrainImagesClassifier(libsvm)" is using an
> average of the polygons or if it is using every single pixel value from the
> polygon for calculation.
>
>
> Thank you very much for the help!
>
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-- 
Manuel Grizonnet

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