Getting hands-on with the code

Now it’s time to get into the code. We’ll go over exactly what C5-face_detection.py does and why each option was chosen. There are five main parts to the code: initialization, image preparation, face detection, face landmarking/aligning, and masking.

Initialization

Let’s begin.

Author’s note

Formatting for easy reading in a book requires modifying the spacing in the samples. Python, however, is whitespace sensitive and uses spacing as a part of the language syntax. This means that copying code from this book will almost definitely contain the wrong spacing. For this reason, we highly recommend pulling the code from the Git repository for the book at https://github.com/PacktPublishing/Exploring-Deepfakes if you plan on running it.

1. First, we import all required libraries:

   import os
   import torch
   import cv2
   import json_tricks
   import numpy as np
   from tqdm import tqdm
   from argparse import ArgumentParser
   from face_alignment...