How to scale face_recognition? about face_recognition HOT 2 CLOSED

If you compile dlib manually with CUDA support (after having installed CUDA and cuDNN), it will use the GPU for generating the face embeddings. So that's a bit faster. However the part that still isn't GPU-accelerated is finding the locations of the faces in each image.

Also the face_recognition script isn't caching anything, so it's rescanning all the known_images each time you run the program which is slower than it needs to be.

One way to speed things up a little bit would be to change the script to pre-cache the face embeddings for each known image and save them somewhere:

1. Cache the results of running face_recognition.face_encodings(unknown_image)[0] on each known image. You only need to do that once.
2. When you want to test an unknown picture, load those cached results into an array called cached_known_faces or something and pass that to face_recognition.compare_faces([cached_known_faces], unknown_face_encoding).

I want to work on improving performance in general, but I haven't had a chance yet.

from face_recognition.

Thanks @ageitgey for the clarification.

from face_recognition.