Re: New RIFE filter - 3x faster AI interpolation possible in SVP!!!
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SmoothVideo Project → Using SVP → New RIFE filter - 3x faster AI interpolation possible in SVP!!!
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read the instructions _carefully_
Please help with this .dll - does it need to be placed somewhere manually?
Try this I think
I tested the fix
- the slow motion bug was fixed
but the TRT on transcode speed is still slower than TRT off, and real time mpv with TRT on didn't work at all.
also
flownet_v4.6.pkl_NVIDIA GeForce RTX 3070 Ti_trt-8.5.2.2_1280x768_fp32_workspace-1073741824_scale-1.0_ensemble-False.pt
isn't it should be FP16?
edit: realtime with mpv is working for now. Still, the speed is slower than TRT off.
> isn't it should be FP16?
replace base.py
> realtime with mpv is working for now
doesn't work for me
"CUDA error: invalid device context"
nothing~~~~~
That one - https://github.com/AmusementClub/vs-mlrt - is MUUUUCH better
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Post updates:
15/01: instructions removed, just install the "TensorRT" package via SVP's "Additional programs and features"
09/01: updated both libs and scripts, should improve 4K performance on 4080+
That one - https://github.com/AmusementClub/vs-mlrt - is MUUUUCH better
The other model (4.6) wont shop up in SVP for me, even after restarting svp and computer.
damn .. too difficult to do something useful in this forum as it seems just one posting per hour is doable or something like this ...
1080P with 4x is possible .. currently creating the files for 4k ... 4k lagging.
transcoding results with TensorRT onnx 4.6 gputhreads=2(and 4-> same results)
1080p -> 117.8 fps
2160p -> 22,4 fps
[vapoursynth] RuntimeError: "C:/Program Files (x86)/SVP 4/rife\models\rife\rife_v4.6.onnx" not found, built-in models can be found at https://github.com/AmusementClub/vs-mlrt/releases
you need put the *.onnx files here C:\Program Files (x86)\SVP 4\rife\models\rife
if there is a black board appear it means you're using TRT ver.
The other model (4.6) wont shop up in SVP for me, even after restarting svp and computer.
those model won't work with RIFE TRT, just ignore them.
RIFE TRT ~83FPS, easy to watch x3 24 1080p in realtime. Compare with vsrife ~60fps
> you need put the *.onnx files here C:\Program Files (x86)\SVP 4\rife\models\rife
yeah, my bad... fixed now
That one - https://github.com/AmusementClub/vs-mlrt - is MUUUUCH better
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Let's try this:0. nothing to do with Python
1. download --> https://www.svp-team.com/files/temp/rife-trt-0701-1.7z <--, unpack into SVP 4\rife (you should already have this folder), so vstrt.dll must be in the root, i.e. SVP 4\rife\vstrt.dll
2. replace generate.js, base.py in SVP 4\script; restart SVP to be sure
3. menu -> Applications settings -> Additional options -> All settings, go to 'User defined options'
Title: TensortRT; Script name: rife_trt; Other values by default - "FRC profile", "ON or OFF"
Click 'Add option'
Go to the RIFE video profile, see the added TensortRT on/off swtich.
Make a copy of the RIFE video profile, one with TensorRT ON and another with OFF.Pros:
- no Pytorch!
- works in a real-time
- even faster (?) than vsrife [could be just because of some TensorRT options]
Cons:
- even slower (?) first-time initialization [could be just because of some TensorRT options]
- a nasty command-line window will pop-up for every new video resolution
Tested this out with an RTX 4090 and seem to be getting around 115fps on a 1080p video. So much better than the default implementation. Used to only get around 80fps with the default
Tested this out with an RTX 4090 and seem to be getting around 115fps on a 1080p video. So much better than the default implementation. Used to only get around 80fps with the default
that's kinda low, Based on the benchmark, 4090 run 1080p should be at ~200fps
> Based on the benchmark
benchmark is for 4.4 model, and I set 4.6 as a default one here
plus note the "GPU threads" option in the video profile, it directly translates into "TRT streams" count
2 and 4 streams have identical performance on my 4090 where k can confirm 115 fps in 1080p. Will try tomorrow with 4.4
Does this help ? https://github.com/AmusementClub/vs-mlr … nt-4623148
I run the 4090 as a pcie 4 card in a pcie 4 x16 slot..
Does this help ? https://github.com/AmusementClub/vs-mlr … nt-4623148
I run the 4090 as a pcie 4 card in a pcie 4 x16 slot..
I'm running mine like that as well, so it doesn't look like that's what's limiting the performance
i tried to investigate with the nvidia monitoring tool ...
https://github.com/AmusementClub/vs-mlr … nt-4624607
> 115 fps in 1080p.
just to be sure - what is the encoding speed with the generic SVP video profile?
I hope you're using H.264/NVENC, not "software" mode as on the screenshot above
try this
just to understand the workflow .. mpv creates a full script based on input from base.py and generate.js and this script is stored under C:\Users\%user%\AppData\Roaming\SVP4\scripts
correct ?
This file does not contain the parameter use_cuda_graph=True and stream maximum is 4 and github user recommends 5 streams to saturate the Ampere GPU - but RTX is already the successor https://github.com/AmusementClub/vs-mlr … nt-4625003
I deleted all models in the appdata folder to make sure they are created from scratch -> with the new generate.js still 22 fps, nothing changed
here's a full script you can use for testing
run with
> vspipe test.py .
variables:
- frame size on line 16, "length" is the number of source frames
- CPU threads on line 6
- GPU streams on line 27
- SVP's add. functions on/off - comment line 69
I thought the problem was in a CPU threads number, which was 4 before, and it's not enough to feed the GPU. Now it's 8, but you're saying there's no difference. Which is strange.
DON'T FORGET TO RESTART SVP after .js/.py file replacing, it may not reload these files automatically in some cases
---
BTW use_cuda_graph=True gives only like 2% difference in my case
Thanks, will invest later tonight how to apply this do you read the github thread ?
---> DON'T FORGET TO RESTART SVP after .js/.py file replacing, it may not reload these files automatically in some cases <---
I just want to report that I got 30fps on 4k transcoding, so it's not SVP problem I think?
rife_v4.6.onnx.3840x2176_fp16_workspace128_trt-8502_NVIDIA-GeForce-RTX-3070-Ti_3dcbe72f.engine
with GPU threads 3
damn .. too difficult to do something useful in this forum as it seems just one posting per hour is doable or something like this ...
1080P with 4x is possible .. currently creating the files for 4k ... 4k lagging.
transcoding results with TensorRT onnx 4.6 gputhreads=2(and 4-> same results)
1080p -> 117.8 fps
2160p -> 22,4 fps
maybe something is wrong with your setup?
my PC is 5900x + 32GB 3600RAM4 C16 + 3070ti, based on average benchmark 4090 is x2 stronger than 3070ti so it should get better result than mine.
SmoothVideo Project → Using SVP → New RIFE filter - 3x faster AI interpolation possible in SVP!!!
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