Add README

Author: mrnugget

README

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+# Train your own OpenCV Haar classifier
+
+## Instructions
+
+1. Get OpenCV
+
+    brew tap homebrew/science
+    brew install --with-tbb opencv
+
+2. Clone this repository
+
+    git clone https://github.com/mrnugget/opencv-haar-classifier-training
+
+3. Put your positive images in the `./positive_images` folder and create a list
+of them:
+
+    find ./positive_images -iname "*.jpg" > positives.txt
+
+4. Put the negative images in the `./negative_images` folder and create a list of them:
+
+    find ./negative_images -iname "*.jpg" > negatives.txt
+
+5. 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"
+
+6. Compile the `mergevec.cpp` file in the `./src` directory:
+
+    cp src/mergevec.cpp ~/opencv-2.4.6/apps/haartraining
+    cd ~/opencv-2.4.6/apps/haartraining
+    g++ `pkg-config --libs --cflags opencv` -I. -o mergevec mergevec.cpp\
+      cvboost.cpp cvcommon.cpp cvsamples.cpp cvhaarclassifier.cpp\
+      cvhaartraining.cpp
+
+7. 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
+
+8. 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
+
+9. 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).
+
+10. Use your finished classifier!
+
+    cd ~/opencv-2.4.5/samples/c
+    chmod +x build_all.sh
+    ./build_all.sh
+    ./facedetect --cascade="~/finished_classifier.xml"
+
+
+## Acknowledgements
+
+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!
+
+## References & Links:
+
+- [Naotoshi Seo - Tutorial: OpenCV haartraining (Rapid Object Detection With A Cascade of Boosted Classifiers Based on Haar-like Features)](http://note.sonots.com/SciSoftware/haartraining.html)
+- [Material for Naotoshi Seo's tutorial](https://code.google.com/p/tutorial-haartraining/)
+- [OpenCV Documentation - Cascade Classifier Training](http://docs.opencv.org/doc/user_guide/ug_traincascade.html)