An open source face recognition engine named SmooFaceEngine.
Let us see something about this project now.
This project is an open source project about face recognition. In the project, we implemented a face recognition engine that was one-shot training.
JUST FOR FUN! I think I may be not a face recognition expert, but a geeker.
In this project, we implemented some CNN, such as VGGNet, VIPL face net, ResNet and XCEPTION etc.
We used AM-Softmax loss as the cost function here, rather than triple loss or other metric learning loss functions. This is because AM-Softmax has less training time, but the accuracy is still good.
This project is a demo. In order to see the experimental results, I trained the model with a small data set. I used data augmentation in this project, so that I can get a robust model. If you want to use this project in your production environment, you should do more.
python train.py
python predict.py
Python 3.5
flask 1.1.1
h5py 2.10.0
Keras 2.3.1
numpy 1.17.1
scipy 1.3.2
tensorflow 1.14.0
You can search the following papers in Google Scholar
AM-Softmax
Sphere face
FaceNet
ResNet
Xception
MobileNet v1,v2,v3
VIPL Face net
- https://github.com/xiangrufan/keras-mtcnn
- https://github.com/happynear/AMSoftmax
- https://github.com/Joker316701882/Additive-Margin-Softmax
- https://github.com/hao-qiang/AM-Softmax
- https://github.com/ageitgey/face_recognition
- https://github.com/oarriaga/face_classification
- https://github.com/seetaface/SeetaFaceEngine
- https://github.com/jiankangdeng/handbook
Apache license version 2.0
There are many bugs here, so you could send some pull requests or give some issues for this project. Thank you very much :)
- give train.py arguments: for different training set
- refactor: to optimize code
- etc.