Exercises

1. We use the mask to cut out the swapped face from the rest of the image but then copy it over to the aligned face. This means that the areas of the aligned image that aren’t the face also get a lower resolution. One way to fix this would be to apply the mask to the original image instead of the aligned image. To do this, you’ll need to call cv2.warpAffine separately for the mask and the aligned image, then use the mask to get just the face copied over. You may want to view the documentation for OpenCV’s warpAffine at https://docs.opencv.org/3.4/d4/d61/tutorial_warp_affine.html.

Be sure to account for the fact that OpenCV’s documentation is based on the C++ implementation, and things can be a bit different in the Python library. The tutorial pages have a Python button that lets you switch the tutorial to using the Python libraries.

2. We rely on pre-extracted faces in order to convert. This is because a lot of the data is already...