Swapping faces

Here comes the last step of the deepfake pipeline, but let's first recap the pipeline. The deepfake production pipeline involves three main stages:

1. Extract a face from an image using dlib and OpenCV.
2. Translate the face using the trained encoder and decoders.
3. Swap the new face back into the original image.

The new face generated by the autoencoder is an aligned face of size 64×64, so we will need to warp it to the position, size, and angle of the face in the original image. We'll use the affine matrix obtained from step 1 in the face extraction stage. We'll use cv2.warpAffine like before, but this time, the cv2.WARP_INVERSE_MAP flag is used to reverse the direction of image transformation as follows:

h, w, _ = image.shape
size = 64
new_image = np.zeros_like(image, dtype=np.uint8)
new_image = cv2.warpAffine(np.array(new_face, 						   dtype=np.uint8)
           ...