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Hi,
You should use TrainVectorClassifier instead of
TrainImagesClassifier. This will train and produce a SVM model
("-io.out" output file). You will have to set (at least) :
- Input Vector Data (io.vd)
- Output model (io.out)
- Field names for training features (feat)
- Field containing the class id for supervision (cfield, in your
case it will be "training")
- Classifier to use for the training (classifier = libsvm)
However, before using this application, you will have to prepare a
vector dataset with only your training polygons (polygons with a
missing value in the field "training" will make the application
crash).
Once you have the output model file (simple text/xml file) you can
use it to do the classification on the full dataset (using
application OGRLayerClassification).
Regards,
Guillaume
On 01/02/2017 11:54 PM, Geoffrey Balme
wrote:
I forgot to say that after the segmentation, I
added a field in my vector attribute table named "training", and
I gave some numeric values to few polygons based on the classes
I want the segments to be classified in (3 classes)
So now I'm with a few polygons having a training value, and most
of the polygon having no training value, and I want to do the
svm classification from this.
Le lundi 2 janvier 2017 23:52:47 UTC+1, Geoffrey Balme a écrit :
Hi Guillaume,
I'm also trying to do supervised object-based
classification.
What I did so far is a meanshift segmentation on my
satellite raster image.
Then I did TrainImagesClassifier (svm) on the vector results
of the segmentation.
And at this point I'm not sure anymore what to do as there
was no output on the previous step.
Could you guide me from the segmentation to have an
object-based classification using SVM ?
(I tried to do OGRLayerClassification, but had no idea of
what to put in the xml inputs etc..., the only input I have
are my raster and my segmentation vector result)
Thank you !
Le jeudi 24 novembre 2016 14:46:00 UTC+1, Guillaume Pasero a
écrit :
Hi Patricia,
If I understand right, you want to perform
object-based classification.
In OTB-5.6.1 there is the application
TrainVectorClassifier to train a classifier based on
input geometries. You have to set several fields in
the geometries you want to use for training :
- one field to indicate the class of the geometry
- several numeric fields to store the features
attached to geometries.
The fields can be extracted from a raster with
LSMSVectorization and modified with QGis.
After the training, you can either apply the model on
the full set of geometries (with OGRLayerClassifier),
or try to apply it on a raster (with ImageClassifier,
but more difficult).
Regards,
Guillaume
On 11/24/2016 02:09 PM, Patricia Lourenco wrote:
Dear all,
I am new with OTB-Monteverdi 5-6-1.
I want to classify an image based on the
segments created in the LSMVSVectorization (step
4 of the segmentation)using OTB/Monteverdi
versions 5.6.1.
However, I am not being able to do it.
My questions are:
1. Which are the steps that I should take to
do a classification based on segmentation?
2. Which OTB-Application should I use to
select the segments for my classes?
Thank you, in advance, for your help.
Sincerely,
Patricia
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Guillaume
PASERO
Responsable technique
Business Unit E-SPACE & Geo
Information - Département Image &
Applications
CS Systèmes d'Information
Parc de la Grande Plaine - 5, Rue Brindejonc
des Moulinais - BP 15872
31506 Toulouse Cedex 05 - FRANCE
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Guillaume PASERO
Responsable technique
Business Unit ESPACE & GeoInformation -
Département Payload Data & Applications
CS Systèmes d'Information
Parc de la Grande Plaine - 5, Rue Brindejonc des
Moulinais - BP 15872
31506 Toulouse Cedex 05 - FRANCE
+33 561 17 64 21 - [email protected]
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