Hi - I am trying to use my Nano as much as OOB as possible
Its just been re-created using jetpack 4.6
I have been adapting one of the JetsonHacks ideas to my own code involving facial recognition from video with Face_recognition.
I applied the one line code fix to dlib as outlined in
[issues with dlib library - #16 by AastaLLL]
Build a Hardware-based Face Recognition System for $150 with the Nvidia Jetson Nano and Python | by Adam Geitgey | Medium
these relate to dlib 19.16 and 19.17 but it seems to still apply to 19.22
That got face_recognition to use the GPU when model=“cnn” was used
However I am finding the startup time to be horrible
the first call to
face_recognition.face_locations(imageRGB ,model="cnn" ) takes 22 to 25 seconds.
subsequent calls take about 0.3 sec to 0.9 sec for larger images
for the 1st call it doesn’t matter what size the image is
If the model is changed to
model="hog" then the first call to face_recognition.face_locations, and each subsequent takes about 0.6 sec
Similar results for the calls to face_recognition.face_encodings
Model=‘cnn’ initial 2.69 sec then .04sec again size doesn’t seem to affect it too much
Model=‘hog’ initial from 5.5 to 10 sec then .04sec
Over 20 seconds just feels like a timeout issue, probably between face_recognition and dlib, but that just me using ‘the force’
Does anybody have any ideas how to make all these bits play nicely together?
dlib.DLIB_USE_CUDA = True dlib version = 19.22.0 dlib compiled = Nov 14 2021 16:36:45 face_recognition.__version__ = 1.2.3 cv2.__version__ = 4.1.1 camera = Raspberry V2