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)
The "1226model" is dump from matlab code which is from References, this model has 1226 stages.
You must change the code in detection/LearnGAB.cpp:58-64. Because the difference between matlab and OpenCV. You should also change the coefficient in detection/LearnGAB.cpp:262-265 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 common.cpp
BSD 3-Clause
https://github.com/wincle/NPD_python
(It's much slow than C++ implementisn. PR is welcomed)
http://www.cbsr.ia.ac.cn/users/scliao/projects/npdface/index.html