vapoursynth VS unstructured

Since ffmpeg CLI still makes me pull ny hair out, I am going to plug vapoursynth:

https://www.vapoursynth.com/

Its Pythonic video filters... But also so much more: https://vsdb.top/

And Staxrip, which makes such good use of ffmpeg, vapoursynth, and dozens of other encoders and tools that I reboot from linux to Windows just to use it: https://github.com/staxrip/staxrip

git clone https://github.com/vapoursynth/vapoursynth cd vapoursynth ./configure make sudo make install

Are you aware of Vapoursynth? https://www.vapoursynth.com/

I have a few options here to process the individual frames for example using ImageData, which exposes the data as an array of pixels, so you could easily 'borrow' some VapourSynth filters for this:

Does the name AviSynth mean anything to you? If so and you want a similar Linux native tool "inspired" by AviSynth, to quote the website, check out http://www.vapoursynth.com/ Just bear in mind that the scripting language is different.

I'm a total newbie to CUDA. I'm trying to implement NVOF in VapourSynth video processing framework. I got the NVOF context initialized. Next step is the buffers!

Download vapoursynth r57 portable from https://github.com/vapoursynth/vapoursynth/releases it's a 7z file so you should have 7-zip installed

Download and compile vapoursynth 1) Go to vapoursynth’s gihub (https://github.com/vapoursynth/vapoursynth/releases) download/wget the tar.gz 2) extract it with tar -xf 3) cd into the folder 4) sudo ./autogen.sh 5) sudo ./configure 6) sudo make install

Be careful with unstructured:

https://github.com/Unstructured-IO/unstructured/blob/d11c70c...

from: https://github.com/open-webui/open-webui/issues/687

I’ve been looking at this

https://freeling-user-manual.readthedocs.io/en/v4.2/modules/...

at the freeling library in general, also spaCy and NLTK. The chunking algorithms being used in the likes of LangChain are remarkably bad surprisingly.

There is also

https://github.com/Unstructured-IO/unstructured

But I don’t like it, can’t explain why yet.

My intuition is that 1st step is clean sentences and paragraphs and titles/labels/headers. Then probably an LLM can handle outlining and table of contents generation using a stripped down list of objects in the text.

BRIO/BERT summarization could also have a role of some type.

Those are my ideas so far.

Unstructured is the best one I’ve used so far: https://www.unstructured.io

https://www.unstructured.io/ can parse PDFs, then you can feed all of them to Claude, which has a 100k context window.

If the copy & pase method does not work: One approach is to use the functionality of Unstructured to parse the PDF. If need be, it can do OCR on the PDF too if you have Detectron2 installed. After conversion you would still have to save it as an excel file though.

I would check out https://github.com/Unstructured-IO/unstructured (what lang chain uses) or https://github.com/axa-group/Parsr (probably what unstructured copied to get their startup off the ground lol)