Haar Classifier does not work, only one feature seems to be trained.

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II have been trying to use OpenCV to create my own Haar Cascade Classifier to detect cows from images.

• Number of positive images:83 , size 430x 280 px, .bmp format
• Number of negative images:200, size 640x480px

My images aren't of that good a quality:

used this to create the samples:

createsamples.exe -info positive/info.txt -vec vector/vector.vec -num 100000 -w 24 -h 24

used this to train:

haartraining.exe -data cascades -vec vector/vector.vec -bg negative/bg.txt -npos 83 -nneg 200 -nstages 18 -mem 2000 -mode ALL -w 24 -h 24

rem -nonsym

And this is a snippet of the training. I realized only one feature is being used (correct me if I am wrong)

Parent node: 6 Chosen number of splits: 0

Total number of splits: 0

Tree Classifier Stage +---+---+---+---+---+---+---+---+ | 0| 1| 2| 3| 4| 5| 6| 7| +---+---+---+---+---+---+---+---+

0---1---2---3---4---5---6---7

Parent node: 7

* 1 cluster * POS: 7 7 1.000000 NEG: 16 1.80409e-005 BACKGROUND PROCESSING TIME: 16.41 Precalculation time: 0.41 +----+----+-+---------+---------+---------+---------+ | N |%SMP|F| ST.THR | HR |
FA | EXP. ERR| +----+----+-+---------+---------+---------+---------+ | 1|100%|-| 0.882353| 1.000000| 0.062500| 0.043478| +----+----+-+---------+---------+---------+---------+ Stage training time: 0.12 Number of used features: 1

Parent node: 7 Chosen number of splits: 0

Total number of splits: 0

Tree Classifier Stage +---+---+---+---+---+---+---+---+---+ | 0| 1| 2| 3| 4| 5| 6| 7| 8| +---+---+---+---+---+---+---+---+---+

0---1---2---3---4---5---6---7---8

It ran upto 8 stages in less than 3mins !

I used this to convert to an xml file:

haarconv.exe cascades myhaar.xml 24 24

My python code uses this xml and can not detect a cow from the positive data set itself. Where am I going here?