Very much looking forward to following the results John. The police in South Wales in the UK did some tests on facial recognition in high-volume spaces, but they haven't returned my mail yet.
Note that dlib has a CNN face detector built in (you can run it in the code as `--models dlib_cnn`). The CNN is an older model, not on of the more modern SqueezeNet/MobileNet varieties. If you have CUDA installed, it will use your GPU by default. If you want it to run without GPU-support (run on your CPU), you'll need to compile dlib from source. I tried both with and without GPU:
- i7: dlib_cnn ran so slow I couldn't even finish the process. Ie, FPS much less than 1. - 1080ti: dlib_cnn was very fast this way; faster than any of the options in the report. But again, we're talking very powerful GPU; something not likely available at the edge.
Generally I'd be less interested in using dlib_cnn since it's a model from another time, and more interested in recent models from public repositories / papers. With these you'll also get more control on how they're run (CUDA on GPU, OpenVINO on Intel, etc).
Yeah, grab the code from Github (link in the report), follow the setup instructions, and drop your own videos into the vids/in directory (instead of downloading the recommended samples). I'll keep that repo updated & try to improve on quality, to make it easy to test on custom vids.