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In earlier ages, (rejectLevels) returned the stage on which the sample was rejected, because there was an arbatrary value where detections from the last 4 stages were returned. However, that seems stupid, since building a 20 stage classifier should not return windows of stage 16-17 which are rejected there.
Until the backend is properly rewritten and thus rejectLevels gives you the rejection of every single window evaluated, it will be left as is and not working. However internally the overload with the numDetections parameter is already using this bogus vector to store its data.
Levelweights is the confidence value of the classification on that stage only, so for now on the final stage. If it is the same value for each object, then something is wrong, because values tend to change here :)
