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Use the DBFace model to build a face recognition platform

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DBFace

DBFace is a real-time, single-stage detector for face detection, with faster speed and higher accuracy

Version requirements

python ==3.6

pyqt == 5.12

opencv-python == 4.0.1.24

QtAwesome == 0.7.2

torchvision==0.7.0

Our work

We use the DBFace model proposed by DeepBlue Technology to build a face recognition platform.

The GUI part is developed by Pyqt5

Result

Picture mode

Before processing

before

After processing

after

Camera mode

camera

QQ

2908689598


Author

References

  1. Hamid Rezatofighi1, Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression:https://arxiv.org/abs/1902.09630

  2. Xingyi Zhou, Objects as Points:https://arxiv.org/abs/1904.07850

  3. Zili Liu, Training-Time-Friendly Network for Real-Time Object Detection:https://arxiv.org/abs/1909.00700

  4. Zhen-Hua Feng, Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks: https://arxiv.org/abs/1711.06753v4

  5. Mahyar Najib, SSH: Single Stage Headless Face Detector: https://arxiv.org/abs/1708.03979

  6. MobileNet: https://github.com/xiaolai-sqlai/mobilenetv3

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Use the DBFace model to build a face recognition platform

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