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?
