The algorithm model of facenet face recognition is obtained through deep learning, and the backbone network of feature extraction is concept-resnetv1, which is developed from concept network and RESNET, with more channels and network layers, so that each layer can learn more features and greatly improve the generalization ability. The network is deeper, the amount of calculation in each layer is reduced, and the ability of feature extraction is strengthened, so as to improve the accuracy of target classification. On the LFW data set, the accuracy of face recognition reaches 98.40%. In this experiment, mtcnn is introduced into the face detection algorithm. Its backbone network is divided into three convolutional neural networks: p-net, R-Net and o-net. Among them, o-net is the most strict in screening candidate face frames. It will output the coordinates of a human face detection frame and five facial feature points (left eye, right eye, nose, left mouth corner, right mouth corner).

Filename	Size	Update
mtcnn-keras-master	0	2020-03-26
mtcnn-keras-master\LICENSE	1065	2020-03-26
mtcnn-keras-master\README.md	614	2020-03-26
mtcnn-keras-master\detect.py	1035	2020-03-26
mtcnn-keras-master\img	0	2020-03-26
mtcnn-keras-master\img\out.jpg	413467	2020-03-26
mtcnn-keras-master\img\timg.jpg	173231	2020-03-26
mtcnn-keras-master\model_data	0	2020-03-26
mtcnn-keras-master\model_data\onet.h5	1604296	2020-03-26
mtcnn-keras-master\model_data\pnet.h5	57184	2020-03-26
mtcnn-keras-master\model_data\rnet.h5	438312	2020-03-26
mtcnn-keras-master\mtcnn.py	7134	2020-03-26
mtcnn-keras-master\utils.py	6707	2020-03-26

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．