github

deepcam-cn / yolov5-face

  • четверг, 29 апреля 2021 г. в 00:27:58
https://github.com/deepcam-cn/yolov5-face




yolov5-face

在yolov5的基础上增加landmark预测分支,loss使用wingloss,使用yolov5s取得了相对于retinaface-r50更好的性能。

WiderFace测试

  • 在wider face val精度(单尺度最大边输入分辨率:1024
Backbone Easy Medium Hard
yolov5s 95.4% 94.6% 88.2%
Yolov5m 95.8% 95.1% 90.5%
RetinaFace-R50(original image scale) 95.5% 94.0% 84.4%

模型测试下载地址

模型测试效果

References

https://github.com/ultralytics/yolov5

https://github.com/DayBreak-u/yolo-face-with-landmark

https://github.com/xialuxi/yolov5_face_landmark

https://github.com/biubug6/Pytorch_Retinaface