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I am trying to train my own OpenCV Haar Classifier for cup detection.
I have 100 images which contain cup and 400 images which do not contain cup, So,

No of Positive Images = 100

No. of Negative Images = 400

At first I created dat for both of them by

find ./Negative_Images -name '*.jpg' >negatives.dat
find ./Positive_Images -name '*.jpg' >positives.dat

Next, I run the following command to generate samples (I put value for sample 100 as no of my positive images are 100. Is it right? )

perl createtrainsamples.pl positives.dat negatives.dat samples 100 "opencv_createsamples -bgcolor 0 -bgthresh 0 -maxxangle 1.1 -maxyangle 1.1 maxzangle 0.5 -maxidev 40 -w 80 -h 60"

Now 100 samples (*.jpg.vec) are created in samples folder. Next, I run the following command to generate samples.vac

python ./tools/mergevec.py -v samples/ -o samples.vec

mergevec.py found in the tutorial by mrnugget

Now for the next command is "opencv_haartraining",

opencv_traincascade -data classifier -vec samples.vec -bg negatives.dat -precalcValBufSize 2500 -precalcIdxBufSize 2500 -numPos 100 -numNeg 400 -numStages 15 -minhitrate 0.99 -maxfalsealarm 0.5 -w 80 -h 60

I am receiving error Error: Can not get new positive sample

Someone solved it by numPos = noOfPositiveImages*0.9, But it did not work for me

From different sources, I found a formula to calculate the value for numPose.

vec-file has to contain >= (numPose + (numStages-1) * (1 - minHitRate) * numPose) + S

So far I understand, for me

vec-file has to contain = 100 (As I had 100 positive Images, and from those 100 samples were created)

numStage = 4 (Or it can be any other value, as I want)

minHitRate = 0.99

S = count of samples from vec-file.(Some other place says, the count of all the skipped samples from vec-file (for all stages))

I do not understand, what value should I put for S?

Can anyone explain this formula with example? What value should I put in the command to solve this error?