aidlearning / wing-loss

A facial landmarks regressor

Wing Loss

This is an implementation of the loss function from
Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks.

How to use a pretrained model

1. Download a pretrained model from here.
2. See an example of usage in inference/try_detector.ipynb.

Example

Notes

1. I didn't train on any datasets in the paper.
2. I simply trained on CelebA dataset (it has five landmark locations for each face).
3. I use a detector from here to detect faces.
4. The inference speed is ~0.15 ms per image (video card is NVIDIA GeForce GTX 1080 Ti, batch size is 8).
5. I used procrustes analysis for data balancing (see data/explore_and_prepare_CelebA.ipynb).

Requirements

1. tensorflow 1.12
2. numpy, Pillow, tqdm