Important: This guide assumes you work with OpenCV 2.4.x. Since I no longer work with OpenCV, and don't have the time to keep up with changes and fixes, this guide is unmaintained. Pull requests will be merged of course, and if someone else wants commit access, feel free to ask!
This repository aims to provide tools and information on training your own OpenCV Haar classifier. Use it in conjunction with this blog post: Train your own OpenCV Haar classifier.
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Install OpenCV & get OpenCV source
brew tap homebrew/science brew install --with-tbb opencv wget http://downloads.sourceforge.net/project/opencvlibrary/opencv-unix/2.4.9/opencv-2.4.9.zip unzip opencv-2.4.9.zip
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Clone this repository
git clone https://github.com/mrnugget/opencv-haar-classifier-training
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Put your positive images in the
./positive_images
folder and create a list of them:find ./positive_images -iname "*.jpg" > positives.txt
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Put the negative images in the
./negative_images
folder and create a list of them:find ./negative_images -iname "*.jpg" > negatives.txt
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Create positive samples with the
bin/createsamples.pl
script and save them to the./samples
folder: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 40"
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Compile the
mergevec.cpp
file in the./src
directory:cp src/mergevec.cpp ~/opencv-2.4.9/apps/haartraining cd ~/opencv-2.4.9/apps/haartraining g++ `pkg-config --libs --cflags opencv | sed 's/libtbb\.dylib/tbb/'`\ -I. -o mergevec mergevec.cpp\ cvboost.cpp cvcommon.cpp cvsamples.cpp cvhaarclassifier.cpp\ cvhaartraining.cpp\ -lopencv_core -lopencv_calib3d -lopencv_imgproc -lopencv_highgui -lopencv_objdetect
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Use the compiled executable
mergevec
to merge the samples in./samples
into one file:find ./samples -name '*.vec' > samples.txt ./mergevec samples.txt samples.vec
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Start training the classifier with
opencv_traincascade
, which comes with OpenCV, and save the results to./classifier
:opencv_traincascade -data classifier -vec samples.vec -bg negatives.txt\ -numStages 20 -minHitRate 0.999 -maxFalseAlarmRate 0.5 -numPos 1000\ -numNeg 600 -w 80 -h 40 -mode ALL -precalcValBufSize 1024\ -precalcIdxBufSize 1024
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Wait until the process is finished (which takes a long time — a couple of days probably, depending on the computer you have and how big your images are).
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Use your finished classifier!
cd ~/opencv-2.4.9/samples/c chmod +x build_all.sh ./build_all.sh ./facedetect --cascade="~/finished_classifier.xml"
A huge thanks goes to Naotoshi Seo, who wrote the mergevec.cpp
and
createsamples.cpp
tools and released them under the MIT licencse. His notes
on OpenCV Haar training were a huge help. Thank you, Naotoshi!