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13th December 2018, 12:45 | #81 | Link |
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@Wolfberry & @WolframRhodium, thank you both kindly for your great assistance! I finally got it working! My, that was a lot of sweat for just bilateralGPU.dll. But the good news is, I went from 2.9 fps to 4.78 fps (including the vspipe to x264 process, of course); and I can visually see (GPU-Z) my video card getting taxed more. So, gentlemen, this was well worth the effort! So, thank you both again.
I'm not sure the forum rules would allow such a thing, but, if so, would be nice if the starter post could contain a link to a small 'dependency' repository for bilateralGPU. I know it's just 1 filter, but debanding is something I'm sure a lot of ppl are doing (because of compression), and with the big GPU's out there, I can attest that it's definitely a worthwhile filter. And for ppl who didn't have those dependencies, some of those are impossible to find on the net. P.S. Actually, the whole 'Dllref = ctypes.windll.LoadLibrary' trick didn't work for me. I simply put core.std.LoadPlugin ("C:/VS/cuda/bilateralGPU.dll"), and had stuck all dependencies inside the C:/VS/cuda/ folder (figuring, as expected, that libraries always look inside their own directory for dependencies first, which worked). Again, thank you guys, and especially you, @Wolfberry. I know I tend to ask a lot of questions, but you made me very happy today, and I'm pretty sure others will be happy with the result too.
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13th December 2018, 13:49 | #82 | Link |
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So these two links contains all dependencies for bilateralGPU? Can't test myself.
https://mega.nz/#!3ygkwKIA!Oa1vAO9FK..._IMddHZeSEcAeA https://mega.nz/#!ejAUSCjD!x-s9Aqr95...9JEroASOJY0bt8
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13th December 2018, 14:32 | #83 | Link |
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This one is needed, too.
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17th December 2018, 02:19 | #84 | Link |
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Speaking of GradFun3, I'm really loving the GPU-assisted speed. GradFun3 doesn't come with presets, though. Usually I did:
vid = core.f3kdb.Deband (vid, preset="medium", dither_algo=2) What settings could I use on GradFun3 to achieve a similar strength as on f3kdb.Deband? In its default state, the debanding of GradFun3 is too little, for my taste.
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17th December 2018, 03:03 | #85 | Link | |
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Quote:
Last edited by WolframRhodium; 17th December 2018 at 09:35. |
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18th December 2018, 11:12 | #87 | Link |
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After several days of testing, I hate to admit that vid = core.f3kdb.Deband (vid, preset="medium", dither_algo=2) does a much better job of preserving the gradients than, for example, vid = fvs.GradFun3 (src=vid, thr=0.6, radius=16, elast=4.0, smode=5), even though the loss of non GPU-assisted processing is felt dearly. Dunno, but for some reason x264 just eats thru GradFun3 like crazy (and I use x264 with very high settings, for quality). Feels like the pattern of f3kdb.Deband is just more compression-resilient somehow. Unless I'm doing GradFun3 wrong, of course (always a possibility).
So, here's to hoping f3kdb.Deband gets ported to GPU one day!
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18th December 2018, 12:13 | #88 | Link | |
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Quote:
The x264 process usurps about 85-92%; vspipe around 1.7% (max). Which means the x246 process doesn't get enough data fast enough to fully saturate the CPU. The whole vspipe process (with x264) takes around 93% CPU, on average. In practice, this means I process around 2.95 fps with f3kdb (as last in the chain), and ca. 4.25 fps with bilateralGPU-assisted GradFun3. The script itself is nothing special; like: Code:
import vapoursynth as vs core = vs.get_core () core.max_cache_size = 16384 core.avs.LoadPlugin ("C:/Program Files (x86)/dgdecnv/x64 Binaries/DGDecodeNV.dll") vid = core.avs.DGSource (r'f:\jobs\jup.dgi', resize_w=1920, resize_h=1080, fulldepth=True) vid = core.dghdrtosdr.DGHDRtoSDR (clip=vid, fulldepth=False) vid = core.avs.DGDenoise (vid, strength=0.1, searchw=9) vid = core.f3kdb.Deband (vid, preset="medium", dither_algo=2) vid.set_output () Versus GradFun3: Code:
import vapoursynth as vs import fvsfunc as fvs core = vs.get_core () core.max_cache_size = 16384 core.avs.LoadPlugin ("C:/Program Files (x86)/dgdecnv/x64 Binaries/DGDecodeNV.dll") core.std.LoadPlugin ("C:/VS/cuda/bilateralGPU.dll") vid = core.avs.DGSource (r'i:\jobs\jup.dgi', resize_w=1920, resize_h=1080, fulldepth=True) vid = core.dghdrtosdr.DGHDRtoSDR (clip=vid, fulldepth=False) vid = core.avs.DGDenoise (vid, strength=0.1, searchw=9) vid = fvs.GradFun3 (src=vid, thr=0.6, radius=16, elast=4.0, smode=5) vid.set_output () 2.95 fps vs. 4.25 fps may not seem like much, but it's the difference between roughly waiting 16 hours before job-completion, or a full 24.
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18th December 2018, 17:40 | #89 | Link | ||
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18th December 2018, 19:02 | #90 | Link | |
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Quote:
What you're saying sounds very logical, though: 10-bit encoding should work wonders for gradients. And without a debanding filter, things go much faster still (ca. 5.15 fps). My next encode can start in about 6 hours. I shall try out a 10-bit conversion, and will report back. Thanks.
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19th December 2018, 01:22 | #91 | Link |
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New update, see first post.
I used my build script this time. I hope everything works: https://github.com/theChaosCoder/vap...rtable-FATPACK
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30th December 2018, 15:11 | #92 | Link | |
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Quote:
Would it be possible to add the new cunet waifu2x models in the next update? |
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30th December 2018, 18:03 | #93 | Link |
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If the models are compatible with the VS version of waifu2x, sure.
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1st January 2019, 08:39 | #94 | Link | |
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Love this pack, thanks!
Quote:
You could even add a few of the upscaling models with presets, but that's kinda a stretch since they're big files. Also, I'm not sure which ones are best to add yet... Need more testing. Another small request: ffmpeg, just for a GPU encoding preset. GPU 10-bit hevc isn't so bad these days, especially if speed is a priority. |
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1st January 2019, 10:47 | #95 | Link |
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Hmm I don't really want to ship a big chunk of dependencies that only nvidia users can use and since I only have a amd card here I can't test it myself. But I could link to a zip package similar to the bilineargpu plugin...
I think I can at least add some bat or vseditor-templates for ffmpeg (gpu) encoding. You use NVenc I guess?
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1st January 2019, 15:52 | #96 | Link | |
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Quote:
Also, there's a mxnet package that supports either Intel CPUs or Nvidia GPUs, depending on which is available. It's not too big, so I don't think it would hurt to include it: https://pypi.org/project/mxnet-cu92mkl/ AMD support for MXNet is coming soon, AFAIK... I'm on an Nvidia GPU atm, so in the meantime I can help test if you want. Last edited by brucethemoose; 1st January 2019 at 19:03. |
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28th January 2019, 16:43 | #97 | Link | |
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Quote:
(don't use it if you have vapoursynth already installed) Code:
Windows Registry Editor Version 5.00 [HKEY_LOCAL_MACHINE\SOFTWARE\Classes\CLSID\{58F74CA0-BD0E-4664-A49B-8D10E6F0C131}] @="VapourSynth" [HKEY_LOCAL_MACHINE\SOFTWARE\Classes\CLSID\{58F74CA0-BD0E-4664-A49B-8D10E6F0C131}\InProcServer32] @="D:\\VapourSynth64Portable\\VapourSynth64\\VSVFW.dll" "ThreadingModel"="Apartment" [HKEY_LOCAL_MACHINE\SOFTWARE\Classes\AVIFile] [HKEY_LOCAL_MACHINE\SOFTWARE\Classes\AVIFile\Extensions\VPY] @="{58F74CA0-BD0E-4664-A49B-8D10E6F0C131}"
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AVSRepoGUI // VSRepoGUI - Package Manager for AviSynth // VapourSynth VapourSynth Portable FATPACK || VapourSynth Database Last edited by ChaosKing; 28th January 2019 at 17:22. |
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1st February 2019, 20:55 | #98 | Link | ||
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Why I'm getting this error?!
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script: Quote:
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1st February 2019, 22:00 | #99 | Link |
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Remove libfocus-em64t.dll and try again. There are currently 2 TemporalSoften dlls with the same namespace inside the plugins folder. (VapourSynth64Portable\VapourSynth64\vapoursynth64\plugins)
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