[INFO] low processor usage - reason?

[Selur]

The Filter combination you chose also uses a lot of ram on higher resolutions.
Using a 1280x720 source ant:

# Imports
import os
import sys
import vapoursynth as vs
core = vs.get_core()
# Import scripts folder
scriptPath = 'I:/Hybrid/64bit/vsscripts'
sys.path.append(os.path.abspath(scriptPath))
# Loading Plugins
core.std.LoadPlugin(path="I:/Hybrid/64bit/vsfilters/Support/libmvtools.dll")
core.std.LoadPlugin(path="I:/Hybrid/64bit/vsfilters/DeCrawlFilter/DotKill/dotkill64.dll")
core.std.LoadPlugin(path="I:/Hybrid/64bit/vsfilters/SourceFilter/LSmashSource/vslsmashsource.dll")
# Import scripts
import hysteria
import hnwvsfunc
import mvsfunc
# Loading E:\to convert\test.mkv using LWLibavSource
clip = core.lsmas.LWLibavSource(source="E:\to convert\test.mkv", format="YUV420P8", cache=0)
# making sure input color matrix is set as unspec
clip = core.resize.Point(clip, matrix_in_s="unspec",range_s="limited")
# making sure frame rate is set to 24000/1001
clip = core.std.AssumeFPS(clip, fpsnum=24000, fpsden=1001)
# Setting color range to TV (limited) range.
clip = core.std.SetFrameProp(clip=clip, prop="_ColorRange", intval=1)
# DeCrawling using DotKill
clip = core.dotkill.DotKill(clip=clip, napply=3)
# removing grain using MLDegrain
clip = hnwvsfunc.MLDegrain(clip=clip, soft=[0,0,0])
# sharpening using FineSharp
clip = hnwvsfunc.FineSharp(clip=clip)
# line darkening using Hysteria
clip = hysteria.Hysteria(clip=clip,highthresh=10)
# Output
clip.set_output()

the memory usage is sky rocketing,... looks like one of the filters has a memory leak.
After ~10min, the RAM usage is > 11 GB and still increasing, so my guess is that if the same is happening on your system, you might run out of RAM.

Cu Selur

Ps.: I'll do some more testing and may be add an option to Hybrid to limit the RAM usage of Vapoursynth.
PPs.: CPU usage is down to 40% now that ~16GB are used,.. my guess is that one of the filters has a bug uses more and more memory and slows down the more memory it uses (hitting 17GB now).