[BUG] Problem with QTGMC + EdiExt + Def + more

[papageno]

Hello everyone,

Thank you very much for creating such a great tool, and for maintaining it over the years. It is greatly appreciated.
I'm writing here in this forum to ask for your help with a couple of problems that I can't seem to solve.

problem 1: 
When I use the 'def' option in QTGMC, it doesn't work. I get an error message that I don't know how to resolve or what causes it. (The process stops when I start it and does not process anything.)




Here is the message that appears at the bottom of the Vapoursynth Editor.

2025-09-21 03:37:24.733
VapourSynth plugins manager: Failed to load vapoursynth library!
Please set up the library search paths in settings.
2025-09-21 03:37:46.578
Failed to evaluate the script:
Python exception: Degrain1: failed to retrieve first frame from super clip. Error message:
Traceback (most recent call last):
File "src/cython/vapoursynth.pyx", line 3207, in vapoursynth.publicFunction
File "src/cython/vapoursynth.pyx", line 3209, in vapoursynth.publicFunction
File "src/cython/vapoursynth.pyx", line 832, in vapoursynth.FuncData.__call__
File "C:\Program Files\Hybrid\64bit\Vapoursynth\Lib\site-packages\vs_deepdeinterlace\DeF.py", line 131, in process_frame
output_img = inference(arrays, even_values, model, device, fp16)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Program Files\Hybrid\64bit\Vapoursynth\Lib\site-packages\vs_deepdeinterlace\DeF.py", line 85, in inference
re_frame = model(input).cpu()
^^^^^^^^^^^^
File "C:\Program Files\Hybrid\64bit\Vapoursynth\Lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Program Files\Hybrid\64bit\Vapoursynth\Lib\site-packages\torch\nn\modules\module.

Traceback (most recent call last):
File "src/cython/vapoursynth.pyx", line 3378, in vapoursynth._vpy_evaluate
File "src/cython/vapoursynth.pyx", line 3379, in vapoursynth._vpy_evaluate
File "C:\Temp\Hybrid-temp\tempPreviewVapoursynthFile03_37_24_564.vpy", line 59, in
clip = qtgmc.QTGMC(Input=clip, Preset="Slower", InputType=0, TFF=True, TR2=1, SourceMatch=3, Lossless=1, MatchPreset="Slower", MatchPreset2="Slower", opencl=True, EdiExt=clipEdiExt) # new fps: 29.97
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Program Files\Hybrid\64bit\vsscripts\qtgmc.py", line 914, in QTGMC
degrain1 = core.mv.Degrain1(edi, ediSuper, bVec1, fVec1, thsad=ThSAD1, thscd1=ThSCD1, thscd2=ThSCD2) # 0.00 0.33 0.33 0.33 0.00
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "src/cython/vapoursynth.pyx", line 3114, in vapoursynth.Function.__call__
vapoursynth.Error: Degrain1: failed to retrieve first frame from super clip. Error message:
Traceback (most recent call last):
File "src/cython/vapoursynth.pyx", line 3207, in vapoursynth.publicFunction
File "src/cython/vapoursynth.pyx", line 3209, in vapoursynth.publicFunction
File "src/cython/vapoursynth.pyx", line 832, in vapoursynth.FuncData.__call__
File "C:\Program Files\Hybrid\64bit\Vapoursynth\Lib\site-packages\vs_deepdeinterlace\DeF.py", line 131, in process_frame
output_img = inference(arrays, even_values, model, device, fp16)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Program Files\Hybrid\64bit\Vapoursynth\Lib\site-packages\vs_deepdeinterlace\DeF.py", line 85, in inference
re_frame = model(input).cpu()
^^^^^^^^^^^^
File "C:\Program Files\Hybrid\64bit\Vapoursynth\Lib\site-packages\torch\nn\modules\module.py", line 1751, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Program Files\Hybrid\64bit\Vapoursynth\Lib\site-packages\torch\nn\modules\module.

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Problem 2 : I am trying to replicate this flow in hybrid, but I cannot figure out how to generate the VFR times and then insert them into the final container.

4-Step Workflow
1️⃣ TFM + TDecimate → CFR + Timecodes

• Generate a progressive (CFR) clip and a timecodes file for VFR.
  
• No AI is applied at this stage.
  

2️⃣ Apply AI (DEF / vs_deepdeinterlace) 

• Use the AI model to remove ghosting, shimmer, and improve frame quality.
  
• This is applied on the CFR clip generated from step 1.
  

3️⃣ Render the AI-enhanced video

• Export a clean, progressive MKV/MP4 with all visual improvements.
  

4️⃣ Reapply VFR using the timecodes

• Use the timecodes file to reconstruct the final VFR video, preserving the original timing and rhythm.
  
• Example with
  
  mkvmerge -o final_output.mkv --timestamps 0:timecodes.txt video_ai.mkv

How can I do the same thing in Hybrid? What is the most reliable method that provides the best quality? And can it be accelerated with a powerful nvidia GPU?.

Thank you very much for your time. I hope someone can help me.