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Model="I:/Hybrid/64bit/vsfilters/ResizeFilter/VSGRAN/models/4x_xbrz_90k.pth",Ĭlip = vsgan_n(clip=clip, chunk=True)
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# Setting color range to TV (limited) range.Ĭlip = (clip=clip, prop="_ColorRange", intval=1) # making sure input color matrix is set as 470bgĬlip = (clip, matrix_in_s="470bg",range_s="limited")Ĭlip = (clip, fpsnum=25, fpsden=1)
# Loading C:/Users/Selur/Desktop/5000frames.mp4 using LWLibavSourceĬlip = (source="F:/TestClips&Co/files/5000frames.mp4", format="YUV420P10", cache=0, prefer_hw=0)
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Python.exe -m pip install torch=1.4.0 torchvision=0.5.0 -f Installed torch (inside the Vapoursynth64 folder) I'm having a bit of trouble working it out right now but hopefully I or someone else, figures out a way to do so. This is an ESRGAN port, so it will generate results the exact same as ESRGAN, and use the same amount of memory as ESRGAN.īut yes, generally speaking x1080 resolution content require quite a bit of memory, i'm trying to work out a way to split up the input frame into multiple split images, to then run them all separately and then combine them back to 1 frame and return, that way using the same amount of memory, but less memory simultaneously, would be slower, but would be the only viable option for most GPU's.
The "spongebob model" looked also not bad for some older animes but had some blurry spots for some reason. I tested some filters and the most usefull (and safe) one which also does not generate artifacts was 1x_DeSharpen.
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Tried to allocate 1.48 GiB (GPU 0 8.00 GiB total capacity 2.56 GiB already allocated 72.05 MiB free 3.65 GiB cached) Does it really need what much ram? used model 1x_DeSharpenĬUDA out of memory.
#Gpu caps viewer 1.5.0 1080p#
I get out of memory errors for 1080p content using a GTX 1070.
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