OGRLayerClassifier

Brief Description

Classify an OGR layer based on a machine learning model and a list of features to consider.

Tags

Segmentation

Long Description

This application will apply a trained machine learning model on the selected feature to get a classification of each geometry contained in an OGR layer. The list of feature must match the list used for training. The predicted label is written in the user defined field for each geometry.

Parameters

• Name of the input shapefile (inshp): Name of the input shapefile

• XML file containing mean and variance of each feature. (instats): XML file containing mean and variance of each feature.

• Input model filename. (insvm): Input model filename.

• Features (feat): Features to be calculated

• Field containing the predicted class. (cfield): Field containing the predicted class

• Load otb application from xml file (inxml): Load otb application from xml file

• Save otb application to xml file (outxml): Save otb application to xml file

Limitations

Experimental. Only shapefiles are supported for now.

Authors

David Youssefi during internship at CNES

See also

ComputeOGRLayersFeaturesStatistics

Example of use

• Values for GUIs:

• inshp: vectorData.shp

• instats: meanVar.xml

• insvm: svmModel.svm

• feat: perimeter

• cfield: predicted

• Command line to execute:

otbcli_OGRLayerClassifier -inshp vectorData.shp -instats meanVar.xml -insvm svmModel.svm -feat perimeter -cfield predicted