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vmafossexec -- a C++ "Wrapper" Executable

The VDK package combines feature extraction implementation in C and the rest scripting code in Python. The Python layer allows fast prototyping, but sometimes deploying the Python dependency in production is a pain. Under wrapper, we provide a C++ implementation vmafossexec that has no dependency on Python.

To build vmafossexec, make the ptools library first, followed by the executable itself:

cd ptools; make; cd ../wrapper; make; cd ..;

Under root, run vmafossexec as:

wrapper/vmafossexec yuv420p 576 324 \
  python/test/resource/yuv/src01_hrc00_576x324.yuv \
  python/test/resource/yuv/src01_hrc01_576x324.yuv \
  model/vmaf_v0.6.1.pkl \
  --log vmaf_output.xml \
  --psnr --ssim --ms-ssim \
  --thread 0 --subsample 5

For VMAF v0.6.1, the model file is model/vmaf_v0.6.1.pkl.

The options --psnr, --ssim and --ms-ssim also allow reporting PSNR, SSIM and MS-SSIM results, respectively. The option --thread specifies the number of threads to use. Apply --thread 0 to use all threads available. The option --subsample specifies the subsampling of frames to speed up calculation. For example, --subsample 5 calculates VMAF on one of every 5 frames. The following plot shows the trend of how the subsample number impacts the processing speed (based on the Netflix Public Dataset of 1080p videos, with PSNR, SSIM and MS-SSIM calculation enabled):

subsample

Optionally, one can test vmafossexec by running the vmafossexec_test.py script (this requires Python 2 and the numpy, scipy, pandas and sklearn packages):

pip install --user numpy scipy pandas sklearn
PYTHONPATH=python/src python python/test/vmafossexec_test.py

Expect all tests pass.