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pvsfunc 4.4.0
pvsfunc
pvsfunc (PHOENiX's VapourSynth Functions) is my compilation of VapourSynth Scripts, Functions, and Helpers.
Installation
Install VapourSynth first! (this is different to the pypi/pip vapoursynth python wrapper!)
pip install --user pvsfunc
Done! However, there are further dependencies listed below that you may need to install depending on the classes you
intend to use, and your use-case. Don't forget to install them if needed!
Building
Building from source requires Poetry.
Simply run poetry install or poetry build for distribution wheel and source packages.
License
This project is released under the GNU GENERAL PUBLIC LICENSE Version 3 (GPLv3) license.
Please read and agree to the license before use, it can be found in the LICENSE file.
Below is information about the projects included in pvsfunc that are available to use. Don't take it as full
documentation as that is being worked on.
PD2V
Convenience class for working with DGIndex D2V project files (MPEG-1/2 videos). Includes source loading, frame
matching, deinterlacing, and more.
Example Usage
from pvsfunc import PD2V
from functools import partial
from havsfunc import QTGMC
clip = PD2V(r"C:\Users\john\Videos\s01e01.d2v", verbose=True).\
ceil().\
deinterlace(
kernel=partial(QTGMC, FPSDivisor=2, Preset="Very Slow"),
verbose=True
).\
clip
# ... any manual changes to clip
clip.set_output()
The above example will load a D2V project file located at C:\Users\john\Videos\s01e01.d2v in Verbose mode.
Verbose mode will display extra information during the PD2V use.
It then runs ceil() which frame-matches the progressive sections of the video with the interlaced sections by
duplicating the progressive frames (instead of interlacing).
It then deinterlaces the interlaced sections of the video with QTGMC as the kernel. The Kernel must have a tff or
TFF argument to be compatible, but the field order should not be manually set by the user.
Finally, it takes the clip and set's it for VapourSynth output.
Dependencies
d2vsource (core.d2v) VapourSynth plugin
DGIndex v1.5.8 or newer
mkvextract Only required if you plan on providing non demuxed streams (e.g., mp4, mkv)
To install d2vsource it's as simple as vsrepo install d2vsource on Windows. Other Operating System user's know the
drill, go check your package repository's or compile it yourself.
Make sure DGIndex and mkvextract is available on your environment path and has execution permissions. Note Linux
Users: Add to system profile path, not terminal/rc path. DGIndex is Windows-only but is supported if you install Wine.
PLS
Convenience class for working with L-SMASH-WORKS LWI project files. Includes source loading and deinterlacing.
More features are to be implemented in the future once a Python-based LWI project parser is available.
Refer to PD2Vs example usage as it's very similar to how PLS is used.
Dependencies
lsmash (core.lsmas) VapourSynth plugin
mkvmerge Only required if input file has a container-set frame rate that differs to the encoded frame rate
To install lsmash it's as simple as vsrepo install lsmas on Windows. Other Operating System user's know the drill,
go check your package repository's or compile it yourself.
Make sure mkvmerge is available on your environment path and has execution permissions. Note Linux Users: Add to
system profile path, not terminal/rc path.
PDebox
Lightweight class to apply de-boxing based on an output aspect-ratio. Similar scripts would annoyingly want you to
just crop in yourself which is incredibly annoying.
PDecimate
Decimate (delete) frames in a specified pattern using cycle and offsets. This is typically used for Inverse-Telecine
purposes.
Decimation may often be done for IVTC purposes to remove constant pattern pulldown frames.
PKernel
Kernel storage class for any custom Deinterlacing kernels I'm working on or tinkering with that you may want to use.
Just know that they are most likely not the type of deinterlacing you may expect, as it's generally a playground for
looking into strange tactics of deinterlacing.
VoidWeave
VoidWeave is a deinterlacing method involving in-painting with machine-learning.
It takes footage and separates the weaved fields so that each field is full-height with the missing data of the field
being 255 RGB green instead of empty/black. The in-painting machine-learning system would then in-paint the missing
data wherever it finds the 255 RGB Green pixels. It works quite well as YUV 4:2:0 DVD data doesn't seem to ever reach
255 green though it does get close, but never quite 255.
I tested it on a Live Action DVD and the results were honestly outstanding! The time it took to run the in-painting
was about the same as QTGMC on Very Slow, with similar results! I think where this method may really shine is with
Cartoon/Animated sources as QTGMC does not do them well.
It all still requires a lot more testing, but it looks like it could be a really nice method! Especially now that I've
learned Disney has also been working on it around the same tim, back in 2020 :P
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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