README

1 Getting Started

1.1 face_recognition

download from dilb ：whms

pip install dlib-19.17.99-cp37-cp37m-win_amd64.whl
pip install face_recognition

1.2 skimage

conda install scikit-image

1.3 tqdm

pip install tqdm

1.4 scipy

download numpy+mkl and scipy from [here](Python Extension Packages for Windows - Christoph Gohlke (uci.edu)).

pip install numpy-1.21.5+mkl-cp37-cp37m-win_amd64.whl
pip install scipy-1.7.3-cp37-cp37m-win_amd64.whl

1.5 pytorch

Just follow the steps on the official website to install.

2 Usage

Place the video files in the video folder and write the names of the videos to be processed in the List_of_testing_videos.txt file.

python face_cut.py -r 512 -t 500 -m 0 -i 5 -s 60 # -b 10

-r ：Resolution of the captured face

-t ：The range of tolerable original face resolution（faces with resolution greater than r-t will be captured and resize to r）

-m ：Crop and alignment，0-VGGface，1-FFHQ

-i ：Initial face capture interval

-s ：Number of skipped frames when no face is detected

-b ：Threshold value for out-of-focus blur detection

The two parameters Max_int = 40 and Min_int = 5 in the file refer to the maximum and minimum values of the dynamic acquisition interval. Increasing Min_int and Max_int decreases the number of face acquisitions and increases the difference between face images.

2 ACK

void_zxh