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m-tassano avatar m-tassano commented on July 21, 2024

Extracts of the script which I use to compute all the scores can be found below. Note that I read the sequences with skvideo.io.vread as grayscale sequences. I basically use pandas to compute the means for all scores for each value of sigma and for each algorithm.

from skvideo.io import vread
from skvideo.measure import viideo_score, strred

...
# open the reference sequence
refseq = vread(seq_ref_path, num_frames=nframes, outputdict={"-pix_fmt": "gray"})

# iterate over the list of sigmas and algorithms
  for sigma, algo in product(sigmaL, algoD.keys()):
    denseq = vread(seq_den_path, num_frames=nframes, outputdict={"-pix_fmt": "gray"})
    _, strred_fr, strred_rr = strred(refseq, denseq)
...
# save all the scores as csv

Later, I use pandas to open csv and compute the mean for each metric. The results are the values which appear in the paper.

from fastdvdnet.

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