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class_yolov5_head

get head bbox by yolov5 in class, which can count class student number and get student whether uphead or downhead

Introduction

class_Yolov5_head_ is a real-time,high accuracy head detection and can classify head pose including uphead and downhead.

Data preparation

  1. get your own data including *.jpg and xml files(label).
  2. use ./data/retinaface2yolo.py to get yolo training dataset from xml files.
python ./data/retinaface2yolo.py
python ./data/val2yolo.py

Training

  1. you can get pretrain model from yolov5-face, and you should set path in train.py. You should set weights as your default pretrain model, set cfg as your yaml file from yolov5-face yaml files.
  2. you can set epoch and batch_size by all you want.

WIDERFace Evaluation

python3 test_widerface.py --weights 'your test model' --img-size 640

cd widerface_evaluate
python3 evaluation.py

Test

  1. you can use detect_face.py to test your model, by images or videos.

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

https://github.com/deepinsight/insightface