<commit_before># NPD

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.
minFaceSize    |  speed(ms)  | cores 
:-----: | :----:    | :----:
80*80 |    30     | 1    
24x24 |    500    | 1
24*24 |   60     | 16

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

# NOTICE

  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:86~96. Because the different between matlab and OpenCV.

# How to use
- you should mkdir data first
<commit_msg>fix README<commit_after># NPD

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.

minFaceSize    |  speed(ms)  | cores 
:-----: | :----:    | :----:
80*80 |    30     | 1    
24x24 |    500    | 1
24*24 |   60     | 16

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

# NOTICE

  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:86~96. Because the different between matlab and OpenCV.

# How to use
- you should mkdir data first

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