/wing-loss

A facial landmarks regressor

Primary LanguageJupyter NotebookMIT LicenseMIT

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

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