The python face_recognition library is a package that can look at a frame, find the faces, encode the found faces, and then compare found face encodings with an array of known face encodings. With a few lines of code it can not only find faces, but accurately determine the identity of the person. The issue is that it appears to not be GPU-friendly, and looks like it runs on the CPU.
Is there a GPU/Cuda friendly equivalent of this package? I know that with the jetson utility and inference packages you can load a frame, and find faces (facenet) quickly, and then display boxed face, but is there a tool that will do the face encoding and comparison on the GPU. If not, what would the path forward be . . . would you do transfer learning, and create a class for each person, and then train on the known faces?
Having a lot of fun learning the Jetson Nano, but want to figure out how to begin to better leverage the GPU. Appreciate any help on this.