I am new to opencv and I am trying to train a classifier using opencv_traincascade command there are number of tutorial I watch and some articles I read but I am confused about some parameter we pass to opencv_traincascade and will be really helpful if someone can explain following is the command I used for training:
opencv_traincascade -data /out -vec /positive/vecfile.vec -bg /negative/negative.txt -w 290 -h 150 -numPos 800 -numNeg 800 -maxFalseAlarmRate 0.45 -featureType LBP -numStages 10
Here is some explanation:
System: Z620 dual Processor with 32 Gb of Ram
OpenCV 3.0
OS: Windows 10 64 bit
-data /out is the output directory
-vec /positive/vecfile.vec vector file having all the positive images
-bg /negative/negative.txt negative txt file containing negative images info
-w 290 width of my object in real time(not sure in what it get measured in opencv like px,cm,mm,inch. in real time it is 290mm)
-h 150 height of my object in real time (not sure in what it get measured in opencv like px,cm,mm,inch. in real time it is 150mm)
numPos 800 number of positive images to train with
numNeg 800 number of negitive images to train with
-maxFalseAlarmRate 0.45 not exactly sure about what it is but it seems to be ratio of wrong detection i think
featureType LBP Algorithm we used to train with
-numStages 10 number of stages the training will go
I am following these steps :
http://doc.openalpr.com/opensource.html#training-the-detector
1) I am confused about the width and height of my object as many examples are using way smaller like 24 width and 24 height or 60 width and 30 height it looks like my width and height values are too high.
2) It is very slow on my xeon machine it suppose to be faster do i need to configure something special about the machine or about opencv.
Please suggest.