2 ms·
That implementation is pretty easy to run! The whole Python block (along with some imports) is something like: clip = core.imwri.Read(img) clip = muf.ssim_dow
by brucethemoose2 4y ago
That implementation is pretty easy to run! The whole Python block (along with some imports) is something like:
clip = core.imwri.Read(img)
clip = muf.ssim_downscale(clip, x, y)
clip = core.imwri.Write(clip, imgoutput)
clip.set_output()
> Any designer will tell you, after down-scaling you do a minimal sharpening pass
This is probably wisdom from bicubic scaling, but you usually dont need further sharpening if you use a "sharp" filter like Mitchell.
Anyway I havent run butteraugli or ssim metrics vs other scalers, I just subjectively observed that ssim_downscale was preserving some edges in video frames that Spline36, Mitchell, and Bicubic were not preserving.