OpenCV / Python : multi-threading for live facial recognition

python multithreading opencv face-detection dlib
Simon picture Simon · Feb 16, 2017 · Viewed 13.7k times · Source

I'm using OpenCv and Dlib to execute facial recognition w/ landmarks, live from the webcam stream. The language is Python. It works fine on my macbook laptop, but I need it to run from a desktop computer 24/7. The computer is a PC Intel® Core™2 Quad CPU Q6600 @ 2.40GHz 32bit running Debian Jessie. The drop in performance is drastic : there is a 10 seconds delay due to processing !

I therefore looked into multi-threading to gain performance :

  1. I first tried the sample code by OpenCv, and the result is great! All four cores hit 100%, and the performance is much better.
  2. I then replaced the frame processing code with my code, and it doesn't improve performance at all ! Only one core hits the 100%, the other ones stay very low. I even think it's worse with multi-threading on.

I got the facial landmark code from the dlib sample code. I know it can probably be optimized, but I want to understand why am I not able to use my (old) computer's full power with multi-threading ?

I'll drop my code below, thanks a lot for reading :)

Answer

Simon picture Simon · Feb 25, 2017

Performance issue was due to a bad compilation of dlib. Do not use pip install dlib which runs very very slowly for some reason compared to the proper compilation. I went from almost 10 seconds lag to about 2 seconds this way. So finally I didn't need multi-threading/processing, but I'm working on it to enhance the speed even more. Thanks for the help :)

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