│   environment_requirements.txt                [Environment file for the required version of libraries]
├── source                                      [Directory: Source code]
│   ├── estimate_mean_face.py                   [Script to estimate mean face from the whole dataset. Required for training] 
│   ├── fill_matrices.py                        [Script to fill matrices and learn the frontalization weights from the dataset]
│   ├── utils.py                                [Collection of helpful functions, including the frontalization function]
│   ├── example_frontalize_dlib_singleimage.py  [Example of applying frontalization on faces from a single image]
│   └── example_frontalize_dlib_camera.py       [Example of applying real-time frontalization on faces from a camera]
└── data                                        [Directory: data, models and sample test images]
    ├── landmark_dataset.csv                    [Dataset of anonymized landmarks with many subjects, headposes and expressions]
    ├── frontalization_weights.npy              [Pre-learnt weights used for the frontalization function]
    ├── landmarks_mean_face.npy                 [Pre-learnt mean face used for the frontalization function] 
    ├── shape_predictor_68_face_landmarks.dat   [DLIB facial landmark model] 
    ├── faces.jpg                               [Example test image] 
    └── demo.gif                                [Example gif showing real-time frontalization]