问题
I am trying my own haar cascade classifier I have 2139 positive images However I have 16000 negative images This is right ? And so I have a negative numPos Because: numPos<=(Positive samples-negative samples)/(1+(stages number-1)(1-minhitrate))) so: (2139-16000)/(1+(17-1)(1-0.995))=-12834 This is normal??
回答1:
no, numPos has nothing to do with your negative samples. numPos is the number of positives you want to use in each stage. This must be a bit lower than your total number of positive samples because you'll lose all the false negatives ( = positive samples which are falsely not detected anymore by the classifier) in each stage.
For example if you sr numPos to 1000 and minHitRate to 0.999 you lose up to 1 positive sample (1000 - 1000*0.999) in each stage. So if you want to compute 2 stages you'll need up to 1001 samples when choosing numPos = 1000.
For 20 stages I roughly choose numPos to be 90% of my positive samples although that is too pessimistic for minHitRate 0.999 (fits 0.995 quite well afair). There is a formula in the openCV Q&A if you want to compute the best/max save value.
来源：https://stackoverflow.com/questions/44337461/can-numpos-be-a-negative-number-in-haar-cascade-training