I got Error during training : Bad argument

[mrnugget]

I got Error during training : Bad argument

[mrnugget]

So how about "Can not get new positive sample. The most possible reason is insufficient count of samples in given vec-file."? Do you have enough samples?

[ktkathi]

I have
positive image : 500 sample
negative image : 500 sample
(size of file: w 200 h 100, file type: png)

and i create sample with this command :
perl bin/createsamples.pl positives.txt negatives.txt samples 500 "opencv_createsamples -bgcolor 0 -bgthresh 0 -maxxangle 1.1 -maxyangle 1.1 maxzangle 0.5 -maxidev 40 -w 200 -h 100"

after i use this command for training:
opencv_traincascade -data classifier -vec samples.vec -bg negatives.txt -numStages 15 -minHitRate 0.995 -maxFalseAlarmRate 0.5 -numPos 500 -numNeg 500 -w 200 -h 100 -mode ALL -precalcValBufSize 1024 -precalcIdxBufSize 1024 -featureType LBP

what wrong parameter that i used it?

Please advice. Thank you.

[mrnugget]

I can't spot something that's obviously wrong. Are you using OpenCV 2.4.9?

[ktkathi]

I try again but it's work no error. What happen? That's true?(see in picture)

[mrnugget]

No idea :)

On Mon, 14 Nov 2016 at 11:23, ktkathi [email protected] wrote:

I try again but it's work no error. What happen? That's true?(see in
picture)
[image: capture]
https://cloud.githubusercontent.com/assets/3676454/20261092/fb0a3f9e-aa8e-11e6-82b8-8c9a5ef384b6.PNG

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[ktkathi]

Hello Mr.Nugget
I'm Finish trained 15 stage and then i follow your description to generate xml file. After i run this command :
./facedetect --cascade="~/finished_classifier.xml"

the result is

is right? where finished_classifier.xml?

and i see in path opencv-haar-classifier-training-master/classifier , i found cascade.xml , params.xml and all stage.xml file. Is this true result?

What file that i use to my android application?

please advice me, Thank you so much.

[mrnugget]

Use the path to casecade.xml instead of the ~/finished_classifier.xml, which is just a placeholder.

[ktkathi]

Thanks a lot ;-)

[mrnugget]

Glad it worked!