efd6b7c39fbefbb1e6f5fdc67ff1d2c64f65d46e,lazyflow/operators/obsolete/classifierOperators.py,OpTrainRandomForest,getOutSlot,#OpTrainRandomForest#Any#Any#Any#,30

Before Change

        // TODO: Make treecount configurable via an InputSlot
        RF=vigra.learning.RandomForest(100)
        try:
            RF.learnRF(featMatrix.astype(numpy.float32),labelsMatrix.astype(numpy.uint32))
        except:
            logger.error( "ERROR: could not learn classifier" )
            logger.error( "featMatrix={}, labelsMatrix={}".format(featMatrix, labelsMatrix) )
            logger.error( "featMatrix shape={}, dtype={}".format(featMatrix.shape, featMatrix.dtype) )
            logger.error( "labelsMatrix shape={}, dtype={}".format(labelsMatrix.shape, labelsMatrix.dtype ) )
            raise

        result[0]=RF

    def setInSlot(self, slot, key, value):
        if self.inputs["fixClassifier"].value == False:

After Change

            requests.append(req)

        for r in requests:
            r.wait()

        return result

    def setInSlot(self, slot, key, value):

Instances