It is an open surce program reference to https://arxiv.org/pdf/1902.10859.pdf , if you find any bugs or anything incorrect,you can notice it in the issues and pull request,be glad to receive you advices.
And thanks @lucknote for helping fixing existing bugs.

WFLW Dataset

​ Wider Facial Landmarks in-the-wild (WFLW) contains 10000 faces (7500 for training and 2500 for testing) with 98 fully manual annotated landmarks.

1. Training and Testing images [Google Drive] [Baidu Drive]
2. WFLW Face Annotations

training :

$ python data/SetPreparation.py
$ train.sh

use tensorboard, open a new terminal

$ tensorboard  --logdir=./checkpoint/tensorboard/

testing:

$ python test.py

Sample images:

Sample gif:

1. The code for cauculating euler angles prediction loss have been added.
2. Fixed the memory leak bug:
   The code has a flaw that i calculate euler angles ground-truth while training process,so the training speed have slowed down because some work have to be finished on the cpu ,you should calculate the euler angles in the preprocess code

If you have any questiones ,please contact us! Also join our QQ group(945933636) for more information.