 How to use  The Face Frontalization model is a saved Pytorch model that can be loaded provided the included *network* package is present in the directory. It takes in 3-channel color images resized to 128x128 pixels in the form of [N, 3, 128, 128] tensors (where N is the size of the batch). Ideally, the input images should be closely-cropped photos of faces, taken in good lighting conditions. Here is how the model can be used for inference with a *gradio* image widget, e.g. in a Jupyter notebook:  ``` import gradio as gr import numpy as np  import torch from torchvision import transforms from torch.autograd import Variable  from PIL import Image import matplotlib.pyplot as plt  import warnings warnings.filterwarnings('ignore')  