I am using a caffemodel (trained for gender classification) with the dnn module of the opencv_contrib library. The issue I am having is that it is running pretty well but it is extremly slow, it takes up to 10 seconds (sometimes) for a face to be processed. I believe the issue is that there is a bottleneck present in the cv::gemm() function - highlighted in this issue https://github.com/opencv/opencv_contrib/issues/490. According to the issue all you need to do is install OpenBLAS or MKL and the performance will increase, I have never used any of those libraries before, hence I am quite unsure how to approach this. Any guidance in regards to increasing the performance or how to setup a solution with OpenBLAS + opencv_contrib will be greatly appreciated.
This is my setup:
- C++ VS 2015
- OpenCV 3.1.0
- Windows 10