testOpTrainClassifierBlocked.py

from builtins import object
import numpy
import vigra

from lazyflow.graph import Graph
from lazyflow.operators.classifierOperators import OpTrainClassifierBlocked
from lazyflow.classifiers import VigraRfLazyflowClassifierFactory, VigraRfLazyflowClassifier

class TestOpTrainRandomForestBlocked(object):
    
    def testBasic(self):
        features = numpy.indices( (100,100) ).astype(numpy.float32) + 0.5
        features = numpy.rollaxis(features, 0, 3)
        features = vigra.taggedView(features, 'xyc')
        labels = numpy.zeros( (100,100,1), dtype=numpy.uint8 )
        labels = vigra.taggedView(labels, 'xyc')
        
        labels[10,10] = 1
        labels[10,11] = 1
        labels[20,20] = 2
        labels[20,21] = 2

        graph = Graph()
        opTrain = OpTrainClassifierBlocked( graph=graph )
        opTrain.ClassifierFactory.setValue( VigraRfLazyflowClassifierFactory(10) )
        opTrain.Images.resize(1)
        opTrain.Labels.resize(1)
        opTrain.nonzeroLabelBlocks.resize(1)
        opTrain.Images[0].setValue( features )
        opTrain.Labels[0].setValue( labels )
        opTrain.nonzeroLabelBlocks[0].setValue(0) # Dummy for now (not used by operator yet)
        opTrain.MaxLabel.setValue(2)
                
        opTrain.Labels[0].setDirty( numpy.s_[10:11, 10:12] )
        opTrain.Labels[0].setDirty( numpy.s_[20:21, 20:22] )
        opTrain.Labels[0].setDirty( numpy.s_[30:31, 30:32] )
        
        trained_classifier = opTrain.Classifier.value
        
        # This isn't much of a test at the moment...
        assert isinstance( trained_classifier, VigraRfLazyflowClassifier )

if __name__ == "__main__":
    import sys
    import nose
    sys.argv.append("--nocapture")    # Don't steal stdout.  Show it on the console as usual.
    sys.argv.append("--nologcapture") # Don't set the logging level to DEBUG.  Leave it alone.
    nose.run(defaultTest=__file__)