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Python 2.x
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OpenCV 2.4.7 or higher (with QT/GTK support, video codec support for the video demo), Python bindings for OpenCV. On a Fedora Linux system, these can be installed with
$ sudo yum -y install opencv python-opencv
- g++ (GNU C++ compiler) version 4.8 or higher or Intel C/C++ compiler (icpc) 12.0 or higher (recommended: icpc 14.0 or higher)
All seven benchmarks are in the apps/ dir. For any of the benchmarks, say camera_pipe/,
camera_pipe_opt.so refers to the fully optimized Polymage code.
camera_pipe_naive.so refers to the base code (naive C code parallelized and
vectorized) and corresponds to PolyMage (base+vec) from the paper.
Set the enviroment variable GOMP_CPU_AFFINITY=0-{NUM_THREADS} for pinning threads to reduce variance between runs
$ make camera_pipe
will build and run the optimized PolyMage code
$ make camera_pipe_naive
will build and run the base code.
$ make graph
will generate a PNG file with the pipeline diagram.
For the video demos, please see video_demo/README.txt