Implementation of PFLD A Practical Facial Landmark Detector by pytorch.
pip3 install -r requirements.txt
- WFLW Dataset Download
โ Wider Facial Landmarks in-the-wild (WFLW) is a new proposed face dataset. It contains 10000 faces (7500 for training and 2500 for testing) with 98 fully manual annotated landmarks.
- WFLW Training and Testing images [Google Drive] [Baidu Drive]
- WFLW Face Annotations
- Unzip above two packages and put them on
./data/WFLW/
- move
Mirror98.txt
toWFLW/WFLW_annotations
$ cd data
$ python3 SetPreparation.py
training :
$ python3 train.py
testing:
$ python3 test.py
PFLD: A Practical Facial Landmark Detector https://arxiv.org/pdf/1902.10859.pdf
Tensorflow Implementation: https://github.com/guoqiangqi/PFLD
-
fix bugs
-
ncnn inference
-
retrain on datasets AFLW and 300W