% Read the target image (person whose face you want to manipulate)
% and the source image (person whose face will be used for the manipulation)
targetImage = imread('path/to/target/image.jpg');
sourceImage = imread('path/to/source/image.jpg');
% Preprocess the images using VGG-Face, VGG-Face-2, or FaceNet
% Note: Replace 'modelName' with the actual model name
% Replace 'preprocessedImageSize' with the actual preprocessed image size
preprocessedTargetImage = preprocess(modelName, targetImage,
preprocessedImageSize);
preprocessedSourceImage = preprocess(modelName, sourceImage,
preprocessedImageSize);
% Use the transfer learning method to transfer the identity from the source image
to the target image
% Note: Replace 'generatorModel' with the actual variable name of your trained
generator model
% Replace 'identityLossFunction' with the actual identity loss function you
are using
transferredTargetImage = generatorModel(preprocessedSourceImage,
identityLossFunction);
% Combine the transferred target image with the preprocessed source image
% to create a deepfake video frame
% Note: Replace 'videoFrameSize' with the actual video frame size
% Replace 'imageStitchingLossFunction' with the actual image stitching loss
function you are using
deepfakeVideoFrame = combineImages(transferredTargetImage, preprocessedSourceImage,
videoFrameSize, imageStitchingLossFunction);
% Save the deepfake video frame as an image file
% Note: Replace 'path/to/save/deepfake/video/frames' with the actual path to save
your deepfake video frames
imwrite(deepfakeVideoFrame, ['path/to/save/deepfake/video/frames/deepfake_frame_'
num2str(frameIndex) '.jpg']);