vs-basicvsr

[Selur]

Cuda plugins very slow now

Not really Cuda, more like most of the ai model based stuff.

[kedautinh12]

You forgot "Cu Selur"

[Selur]

¯\_(ツ)_/¯

[Selur]

A few more examples of vs-femasr:
not bad:
https://imgsli.com/MTQ1ODI3
https://imgsli.com/MTQ1ODI4
https://imgsli.com/MTQ1ODI5
https://imgsli.com/MTQ1ODM1
nice detail recovery, but partially too sharp (too much contrast) for my liking, and if you have noise&co that might get enhanced too.
https://imgsli.com/MTQ1ODM5

Cu
Selur

[Selur]

High Performance GMFSS with RIFE and GAN for Anime Video Frame Interpolation: https://github.com/HolyWu/vs-gmfss_union

[kedautinh12]

Wow, VS development very fast. When i think Avs+ can reach to VS but after Pytorch, NumPy releases VS development more than Avs+ very much

[ChaosKing]

Some quick performance numbers with RTX 3070 TI & 720x480 clip (noisy source):
tested with vsedit, so number should be slighlty higher bcs of the editors small overhead.

gmfss_union(clip) # ~14fps
gmfss_union(clip, trt=True) # ~17fps, tensor cache took a long time to build
gmfss_union(clip, num_streams=2) # ~17.5fps
gmfss_union(clip, num_streams=3) # ~18.9fps
gmfss_union(clip, trt=True, num_streams=2) # ~21.5fps
gmfss_union(clip, trt=True, num_streams=3) # ~22.5fps

[Selur]

What speed do you get with RIFE and the anime model?

[ChaosKing]

https://github.com/HolyWu/vs-rife runs with 175 fps
clip = RIFE(clip)

https://github.com/HomeOfVapourSynth...FE-ncnn-Vulkan
rife.RIFE(clip, model=3) # ~78fps

Look at this perfect frame
https://i.imgur.com/r2GAnRI.jpeg

[Selur]

Okay, so it's really slow.
(for RIFE enabling sc and setting sc_threshold to something like 0.1 might help a bit)

...

Played around with it and probably won't add this to Hybrid since I don't see any gain from it over RIFE&co atm.

[~ VEGETA ~]

tried installing vsbasicvsr++ but got this error: https://pastebin.com/6VWwaXRd

how can i solve it?

[Selur]

Probably an issue with the cuda dependencies,
here's what I did last time I setup the environment:

• I created a new empy Vapoursynth-folder
• downloaded 'Windows embeddable package (64-bit)' from https://www.python.org/downloads/release/python-3108/ (3.11 isn't supported atm. by Vapoursynth)
• extracted the Python download into the download into the 'Vapoursynth'-folder
• downloaded 'VapourSynth64-Portable-R60.7z' from https://github.com/vapoursynth/vapoursynth/releases
• extracted the Vapoursynth portable download into the 'Vapoursynth'-folder
• downloaded get-pip.py from https://bootstrap.pypa.io/get-pip.py and save it into the 'Vapoursynth'-folder
• opened a 'Windows Command Prompt'-window and navigate into the 'Vaporusynth'-folder
• installed pip by calling :
  

  pyhton get-pip.py

• opened the python310._pth in a text addition and added the following to lines above anything else in that file and saved the file
  

  Scripts
  Lib\site-packages

• installed VSGAN
  • python -m pip install vsgan
  • python -m pip install torch===1.13.0+cu117 torchvision==0.14.0 -f https://download.pytorch.org/whl/torch_stable.html
  • installed BASICVSR++
    

    python -m pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu117/torch1.13/index.html
    python -m pip install tqdm
    python -m pip install opencv-python
    python -m pip install --upgrade vsbasicvsrpp
    python -m vsbasicvsrpp

• installted RIFE
  • downloaded https://github.com/HolyWu/vs-realesr...5.2.2_win64.7z (there's a newer versio now)
    
  • extractedtensorrt-8.5.2.2-cp310-none-win_amd64.whl into my Vapoursynth folder
  • python -m pip install tensorrt-8.5.2.2-cp310-none-win_amd64.whl
  • deleted tensorrt-8.5.2.2-cp310-none-win_amd64.whl
  • python -m pip install --upgrade vsrife
  • created a folder 'vsrife_dependencies' inside the Vapoursynth folder and copied the other files form the CUDA-11.7_cuDNN-8.6.0_TensorRT-8.5.1.7_win64.7z into it. This folder need to be added to when using vs-rife using:
    

    import site
    # add vs-rife dependencies to the path
    path = site.getsitepackages()[0]+'/torch_dependencies/'
    path = path.replace('\\', '/')
    import os
    os.environ["PATH"] = path + os.pathsep + os.environ["PATH"]

  • downloaded the models using:
    

    set PATH=i:\Hybrid\64bit\Vapoursynth\torch_dependencies\bin;%PATH
    python -m vsrife

  • installed SWINIR
    

    python -m pip install --upgrade vsswinir
    python -m vsswinir

• installed DPIR and onnxruntime-gpu
  

  python -m pip install --upgrade vsdpir
  python -m pip install --upgrade onnxruntime-gpu
  python -m vsdpir

• created a onnxruntime_dlls folder inside the Vapoursynth folder.
  I copied from cudnn-11.4-windows-x64-v8.2.4.15.zip and NVIDIA CUDA SDK 11.4.1 runtimes the following files into the folder:
  • cublas64_11.dll
  • cublasLt64_11.dll
  • cudart64_110.dll
  • cudnn_cnn_infer64_8.dll
  • cudnn_ops_infer64_8.dll
  • cudnn64_8.dll
  • cufft64_10.dll
  • cufftw64_10.dll
  • msvcp140.dll
  • nvinfer.dll
  • nvinfer_builder_resource.dll
  • nvinfer_plugin.dll
  • nvonnxparser.dll
  • nvparsers.dll
  • vcruntime140.dll
  • vcruntime140_1.dll
• When using vsdir or realesrgan in a Vapoursynth script:
  

  # Import libraries for onnxruntime
  import site
  import ctypes
  path = site.getsitepackages()[0]+'/onnxruntime_dlls/'
  ctypes.windll.kernel32.SetDllDirectoryW(path)

  needs to be added to the script to load the dlls.
• installed REALESRGAN (which also uses onnxruntime)
  

  python -m pip install --upgrade vsrealesrgan
  python -m vsrealesrgan

• Installed HINet
  

  python -m pip install --upgrade vshinet
  python -m vshinet

Cu Selur

Ps.: also send you a link to my current Hybrid dev and torch addon, going to bed now. You might want to checkout