Search options (Page 29 of 354)

UHD
> We are now testing

you are not

aloola
> I just want to report that I got 30fps on 4k transcoding

and you're capped by the encoder speed
try h264 instead
or set preset=fast in 'advanced' mode, cause it's set to "slow" by default

---> DON'T FORGET TO RESTART SVP after .js/.py file replacing, it may not reload these files automatically in some cases <---

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

> 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

> you need put the *.onnx files here C:\Program Files (x86)\SVP 4\rife\models\rife

yeah, my bad... fixed now

> 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"

UHD
I propose to change it: vs.RGBS to vs.RGBH

great advice
updated the post above

aloola
The output video still has the same old FPS and it's in slow motion and the video duration x2.

looks like a vsrife's bug, fixed .py file attached above
https://github.com/HolyWu/vs-rife/issues/22

=== RIFE / PyTorch+TensorRT installation ===

DO NOT DO THIS!
You DON'T NEED IT!
I'm SERIOUS!
============

!!! Advanced users only, if you don't know what this is all about - you don't need it !!!

0. Update SVP via online updater (this will update Python to ver. 3.10.9)

1. Dependencies installation:
--------------
Download TensorRT libs: https://github.com/HolyWu/vs-rife/relea … 2_win64.7z
unpack CUDA-blah-blah.7z to SVP 4\mpv64

run cmd as Administrator

cd SVP 4\mpv64

python get-pip.py

python -m pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/cu117
python -m pip install tensorrt-8.5.2.2-cp310-none-win_amd64.whl
python -m pip install torch-tensorrt-fx-only tqdm
python -m pip install -U --no-deps vsrife
python -m vsrife

A quick fix for vsrife's "slowmo" bug: replace __init__.py in SVP 4\mpv64\Lib\site-packages\vsrife\

2. SVP modification
---------------
Replace SVP 4\script\generate.js and base.py with the attached ones

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.

----------------
For a given video resolution the first-time start is super-slow (while it generates TRT net in a cache folder --> %APPDATA%\SVP4\cache\trt), so better do it in a "transcoding" mode.

SVP тут вообще не при чем.
Всё что "в терминале" - это Homebrew, все претензии туда. Они стабильно поддерживают только ТРИ последние версии ОС, всё что раньше ставить все-равно можно, но будет долго и мрачно собираться из исходников, и без 100% гарантии успеха.

work in progress, but with a low priority cause the current FRUC API only allows x2 interpolation which makes it not so interesting as it could be