Clone this repository and prepare the dataset and weights through the following steps:
a. Prepare model weights for face detection.
Download the weights of dlib face detector of 68 landmarks here. Unzip it and move it to the directory ./faceutils/dlibutils
.
Download the weights of BiSeNet (PyTorch implementation) for face parsing here. Rename it as resnet.pth
and move it to the directory ./faceutils/mask
.
b. Prepare Makeup Transfer (MT) dataset.
Download raw data of the MT Dataset here and unzip it into sub directory ./data
.
Run the following command to preprocess data:
python training/preprocess.py
Your data directory should look like:
data
└── MT-Dataset
├── images
│ ├── makeup
│ └── non-makeup
├── segs
│ ├── makeup
│ └── non-makeup
├── lms
│ ├── makeup
│ └── non-makeup
├── makeup.txt
├── non-makeup.txt
└── ...
c. Download weights of trained EleGANt.
The weights of our trained model can be download here. Put it under the directory ./ckpts
.