Classify an OGR layer based on a machine learning model and a list of features to consider.
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.
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
Experimental. Only shapefiles are supported for now.
David Youssefi during internship at CNES
Example of use
otbcli_OGRLayerClassifier -inshp vectorData.shp -instats meanVar.xml -insvm svmModel.svm -feat perimeter -cfield predicted