PFLD-pytorch

Implementation of PFLD A Practical Facial Landmark Detector by pytorch.

install requirements

pip3 install -r requirements.txt

Datasets

• WFLW Dataset Download

​ 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.

1. WFLW Training and Testing images [Google Drive] [Baidu Drive]
2. WFLW Face Annotations
3. Unzip above two packages and put them on ./data/WFLW/
4. move Mirror98.txt to WFLW/WFLW_annotations

$ cd data 
$ python3 SetPreparation.py

training & testing

training :

$ python3 train.py

testing:

$ python3 test.py

results:

reference:

PFLD: A Practical Facial Landmark Detector https://arxiv.org/pdf/1902.10859.pdf

Tensorflow Implementation: https://github.com/guoqiangqi/PFLD

TODO:

• fix bugs

• ncnn inference

• retrain on datasets AFLW and 300W