Traincascade - Required leaf false alarm rate achieved. Branch training terminated.

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Hi all,

First of all, I know this kind of question was asked thousand times, and believe me I've read them all. Problem is that answers in most cases are very different and/or contradict. I would like to show you what have I done and what result I got and hope for you to show me what is this I do wrong.

NOTE: Example shown below is my latest failure with 100 positive and 200 negative pictures. I also tried 700 pos and 300 neg, 2000 pos and 5000 neg, 8000 pos and 9000 neg. I also tried changing several other options but I will answer your questions as they come.

1) I am trying to make my own car cascade. I am mostly interested in frontal and back view of the car, so I have several thousand positive pictures showing exactly that and negative pictures showing common background, street signs, etc. Both positive and negative pictures are sized 64x64. First, I put all of my positive pictures in my positive folder and all of my negative pictures in my negative folder. Then I run the command to create my positive.txt and my negative.txt file.

Result looks like this:

.\negative_images\image352.png
.\negative_images\image353.png
.\negative_images\image354.png
.\negative_images\image355.png
.\negative_images\image356.png
.\negative_images\image357.png
.\negative_images\image358.png
...

And this:

.\positive_images\image0005.png
.\positive_images\image0006.png
.\positive_images\image0007.png
.\positive_images\image0008.png
.\positive_images\image0009.png
.\positive_images\image0032.png
.\positive_images\image0033.png
.\positive_images\image0034.png
...

2) After that i run Naotoshi Seo's createsamples script to create vec file

bin\createsamples.pl positives.txt negatives.txt samples 300 "F:\opencv3.2.0\build\x64\vc14\bin\opencv_createsamples -bgcolor 0 -bgthresh 0 -maxxangle 1.1 -maxyangle 1.1 maxzangle 0.5 -maxidev 40 -w 64 -h 64"

Number 300 (4th parameter) should be total number of pictures: all positives + all negatives. Is this correct? Does -w and -h parameter values should match pictures width and height?

3) All vec files are now in samples folder. Now i run script to merge all vec files in to one.

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

4) Now I run traincascade to create xml

F:\opencv3.2.0\build\x64\vc14\bin\opencv_traincascade.exe -data classifier -vec samples.vec -bg negatives.txt -numStages 10 -minHitRate 0.999 -maxFalseAlarmRate 0.5 -numPos 100 -numNeg 200 -w 64 -h 64 -mode ALL -precalcValBufSize 6096 -precalcIdxBufSize 6096

And this is the result:

PARAMETERS:
cascadeDirName: classifier
vecFileName: samples.vec
bgFileName: negatives.txt
numPos: 100
numNeg: 200
numStages: 10
precalcValBufSize[Mb] : 6096
precalcIdxBufSize[Mb] : 6096
acceptanceRatioBreakValue : -1
stageType: BOOST
featureType: HAAR
sampleWidth: 64
sampleHeight: 64
boostType: GAB
minHitRate: 0.999
maxFalseAlarmRate: 0.5
weightTrimRate: 0.95
maxDepth: 1
maxWeakCount: 100
mode: ALL
Number of unique features given windowSize [64,64] : 13481422

===== TRAINING 0-stage =====
<BEGIN
POS count : consumed   100 : 100
NEG count : acceptanceRatio    200 : 1
Precalculation time: 69.809
+----+---------+---------+
|  N |    HR   |    FA   |
+----+---------+---------+
|   1|        1|        1|
+----+---------+---------+
|   2|        1|    0.115|
+----+---------+---------+
END>
Training until ...