real time face recognition with MTCNN and FaceNet
you need to do things below:
- I have already uploaded det1.npy det2.npy det3.npy which for MTCNN,but you still need to download facenet's pb file from davidsandberg's github like 20170511-185253,extract to pb file and put in models directory.
- tensorflow-gpu 1.1.0 , later version may also work.
- python 3.X
- OpenFace
- davidsandberg's github
- main code is refered to bearsprogrammer
Remember to change some codes where you need to put your own name and your friends' name instead of mine.
Do as follows step by step:
- To make you easy to get your photo and put in right structure as I said in intput and output directorys' readme.md file,I already privide getphoto.py which can take photos by openCV and autoly put it in input directory as format.
- Next,you need to run Make_aligndata.py to align your photos which only croped your face part and autoly put in output directory as format.This photos will be used to train our own classifier.
- Run Make_classifier.py to train our own classifier with SVM.Of course you can use your own classifier if you want.Then you may see myclassifier.pkl file in myclassifier directory.
- Finally,run realtime_facenet.py or real_time.py. realtime_facenet.py is MTCNN version.real_time.py is another choice which use haar detector in openCV instead of MTCNN.
If everything is ok ,you will see result below:
I used Chinese to do some Introduction about MTCNN and FaceNet.See my blog for details
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent