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LBP model training using traincascade


I am trying to create several new models for objects using the LBP approach so that I could use it inside of the ViolaJones framework to detect other elements than faces.

So far I have succesfully created the vector of possitive samples, and started the training (using traincascade algorithm) with following specific parameters: numPos 35 numNeg 100 numStages 20 featureType LBP -w 36 -h 47 -minHitRate 0.995 -MaxFalseAlarmRate 0.5

It went pretty good until level 15, then each stage took a lot more time to train, which is logical as far as I see it. However, for the moment it seems to gotten stuck at level 17.

Since the algorithm only creates the final XML file after processing all stages, I was wondering if there is any way to create a temporary XML detection model based solely on the first 16 in between xml files? I could not seem to find any guidance on the internet for this problem.