To be able to use Matlab, you need to first successfully download and activate Matlab, as described here. Then, add a line to python/src/vmaf/externals.py, like:
MATLAB_PATH = <path_to_matlab>
For example (mac OSX):
MATLAB_PATH = "/Applications/MATLAB_R2017a.app/bin/matlab"
The available algorithms are ST-MAD [1], ST-RRED [2], SpEED-QA [3] and BRISQUE [4].
Example usage for ST-MAD, ST-RRED and SpEED-QA with the run_testing script:
./run_testing quality_type dataset_file
where quality_type can be STMAD (for ST-MAD), STRRED (for ST-RRED) and SpEED_Matlab (for SpEED-QA). We have also implemented a computationally efficient version of ST-RRED (use STRREDOpt as the quality_type), which produces numerically identical results to ST-RRED.
Example usage for BRISQUE:
./run_vmaf yuv_420p 1920 1080 NFLX_dataset_public/ref/OldTownCross_25fps.yuv NFLX_dataset_public/dis/OldTownCross_90_1080_4300.yuv --model model/vmaf_brisque_all_v0.0rc.pkl
[1] P. V. Vu, C. T. Vu, and D. M. Chandler, "A spatiotemporal mostapparent-distortion model for video quality assessment," IEEE Int’l Conf. Image Process., pp. 2505–2508, 2011.
[2] R. Soundararajan and A. C. Bovik, "Video quality assessment by reduced reference spatio-temporal entropic differencing," IEEE Trans. Circ. Syst. Video Technol., vol. 23, no. 4, pp. 684–694, Apr. 2013.
[3] C. G. Bampis, P. Gupta, R. Soundararajan, and A. C. Bovik, "SpEEDQA: Spatial efficient entropic differencing for image and video quality," IEEE Signal Process. Lett., vol. 24, no. 9, pp. 1333–1337, 2017.
[4] A. Mittal, A. K. Moorthy, and A. C. Bovik, "No-reference image quality assessment in the spatial domain," IEEE Trans. Image Process., vol. 21, no. 12, pp. 4695–4708, Dec. 2012.