The C++ implementation of A Fast and Accurate Unconstrained Face Detector.

The result is trained by 200k pos data and the template is 24*24, stages number is 620, model size is 540kb.

the detection result is test on FDDB data set (average 400*400)

The "1226model" is dump from matlab code which is from References, the model has 1226 stages , if you want to try this model ,you should rename it "result".

You must change the code in detection/LearnGAB.cpp:8696. Because the difference between matlab and OpenCV. You should also change the coefficient in detection/LearnGAB.cpp:276279 to fit the model.

• you should mkdir data first

In data folder, you should creat two file named FaceDB.txt and NonFaceDB.txt.

FaceDB.txt
../data/face/00001.jpg x1 y1 x2 y2
../data/face/00002.jpg x1 y1 x2 y2
....
....

NonfaceDB.txt
../data/bg/000001.jpg
../data/bg/000002.jpg
../data/bg/000003.jpg
....
....

hd.txt(Optional)
../data/hd/000001.jpg
../data/hd/000002.jpg
../data/hd/000003.jpg
...

the hd image is hard negative for init training , the size of it should to be the same with your model template(24 for me).

The config is in src/common.cpp

#TODO

Speed Up the Detection and Training

#License

BSD 3-Clause

http://www.cbsr.ia.ac.cn/users/scliao/projects/npdface/index.html

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