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2015-01-27 02:37:17 -0600	commented question	HAAR training fails at different stages Required leaf false alarm rate doesn't usually mean it has failed. It means it has completed training early than the number of stages you required, check the classifier directory and it should be in there. If not try and increase your -minHitRate parameter
2015-01-27 02:33:31 -0600	received badge	● Editor (source)
2015-01-27 02:32:57 -0600	asked a question	Cascade trained from trainingcascade unaccurate Hi I trained a classifier using 1000 positive female faces from the FERET database and 2500 negative images including male FERET faces and some background images not containing any faces, with the intention of classifying gender. The training was complete after 18 hours/7 training stages and the output classifier gives the results as below. Could anyone explain why and what was wrong with my method? Here are my parameters: `opencv_traincascade -data classifier\ -vec female.vec -bg negative.txt -numStages 12 -minHitRate 0.995 -maxFalseAlarmRate 0.5 -numPos 1000 -numNeg 2500 -w 30 -h 37 -precalcValBufSize 2048 -precalcIdxBufSize 2048 -featureType HAAR`
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2015-01-19 13:06:53 -0600	received badge	● Supporter (source)
2015-01-18 07:53:13 -0600	commented question	Gender recognition Ok thanks I'll take a look!
2015-01-17 10:29:15 -0600	commented question	Gender recognition Thanks Steven, could you elaborate on the alternative method of feature and SVM combination? Any good resources that you know of?
2015-01-16 04:05:44 -0600	asked a question	Gender recognition I've been doing some research and attempted to build a haarcascade for identifying gender. I read this article, which describes how they did it, which i also tried to do : http://www.ijcce.org/papers/301-E043.pdf I used a library of 228 male faces and 350 female faces. Using the opencv createclassifier on my positives.txt file which contains a list of the male faces. Using the .vec file create by the classifier I used haartraining with the following command: `opencv_traincascade -data classifier -vec positivies.vec -bg negatives.txt -numStages 20 -minHitRate 0.99 -maxFalseAlarmRate 0.5 -numPos 228 -numNeg 350 -w 640 -h 480 -mode ALL` After running this a few times I do not get a haar classifier.xml output file so I'm unsure whether I am doing everything correctly. But my question is whether it is possible using male faces as positive samples and female as negative samples to train and use a haarcascade for classifying gender?