Hi,
i am training my own classifier of swivel chairs. But i need some recommendation with training parameters to make it more accurate because i am new with training and would like to hear your recommendation. I have 200 positive images and 500 negative images (both are 300x300). I have used the Naotoshi Seo Pearl script to create samples:
perl bin/createsamples.pl positives.txt negatives.txt samples 1500\
"opencv_createsamples -bgcolor 0 -bgthresh 0 -maxxangle 1.1\
-maxyangle 1.1 maxzangle 0.5 -maxidev 40 -w 80 -h 80"
Here i am not sure about the -w and -h. Would you create smaller samples?
And for training used this parameters:
opencv_traincascade -data classifier -vec samples.vec -bg negatives.txt -numStages 20
-minHitRate 0.999 -maxFalseAlarmRate 0.5 -numPos 1000 -numNeg 500 -w 80 -h 80 -mode ALL
-precalcValBufSize 1024 -precalcIdxBufSize 1024 -featureType LBP
It is still training and on the stage 15 i am getting this numbers:
===== TRAINING 15-stage =====
<BEGIN
POS count : consumed 1000 : 1000
NEG count : acceptanceRatio 500 : 0.00114124
Precalculation time: 48
+----+---------+---------+
| N | HR | FA |
+----+---------+---------+
| 1| 1| 1|
+----+---------+---------+
| 2| 1| 1|
+----+---------+---------+
| 3| 1| 1|
+----+---------+---------+
| 4| 1| 0.86|
+----+---------+---------+
| 5| 1| 0.716|
+----+---------+---------+
| 6| 1| 0.528|
+----+---------+---------+
| 7| 1| 0.346|
+----+---------+---------+
END>
I would gladly hear some others opinions on this training so i can learn from experienced people. Thank you very much for any responses.