TrainImagesClassifier and TrainVectorClassifier perform training but on
different inputs.

TrainImagesClassifier takes as input one or multiple images and separately
polygons with class label associated to each polygon. Pixels inside those
polygons will be used to create the training set

The TrainVectorClassifier should be used in the case where you've only a
vector file which contains positions and values which corresponds to sample
values for each position (for instance a vector layer of points).
TrainVectorClassifier is used for instance in the sampling processing where
after extracting pixel positions and values, the vector of points obtain is
used as input for the TrainVectorClassifier.

I would advise to follow the "Pixel based classification" recipe in the
cookbook:

<goog_903394397>
https://www.orfeo-toolbox.org/CookBook/recipes/pbclassif.html#pixel-based-classification

You'll be able to use as input multiple images and multiple shapefiles at
the same time for the training.


Le ven. 14 sept. 2018 à 13:47, Efi <[email protected]> a écrit :

> Dear All,
>
> I want to perform object-based classification on SAR images for oil spill
> detection. The OTB tools I intend to use are TrainVectorClassifier and
> VectorClassifier. As I understand so far, The tool TrainVectorClassifier
> takes  input polygons only form ONE layer, as opposed to the tool
> TrainImagesClassifier that accepts input from more than one layers. Since
> oil spills can significantly vary in size and shape (ex. see attached
> images), I was wondering if there is a way to provide data from more than
> one layers when applying TrainVectorClassifier. Any help and ideas will be
> appreciated,
> Best,
> Liten
>
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-- 
Manuel Grizonnet

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