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View Code? Open in Web Editor NEWturn your messy media archive into a personal streaming service, photo viewer, and searchable library.
License: GNU Affero General Public License v3.0
turn your messy media archive into a personal streaming service, photo viewer, and searchable library.
License: GNU Affero General Public License v3.0
generic
, image_gallery
, tv_shows
, movies
, documents
and each one displays the results in a different way.If a file is detected as a YouTube video, import SponsorBlock data and store it as segments for that video so ads can be easily skipped.
Show GPS locations on a map so you can have a view of where your photos are from.
Moving or changing files slightly should copy over metadata if the files are mostly the same
Let users pick images that represent tags, and images that do not. Using CLIP vectors we can then do a pretty naive check by using similarity to determine if that image belongs in the tag or not, by seeing how close it is to the "in this tag" and how close it is to the "not in this tag" groups.
The user could configure a similarity required to match, and a similarity required to not match.
Specifically portrait_8.jpg
in the exif test set, the thumbhash is square but the resulting image is rectangular and it's not even close to accurate. I was hoping this was fixed by passing in the aspect ratio to thumbhash but I think it takes that as more of a suggestion.
Let the user provide "templates", which are applied to files as a faster alternative to LLM extraction or other methods.
{title} ({year}) [imdbId-{imdbId}]
which is then converted into regex. Each property comes with a regex pattern that is pulled in, eg
/^[0-9A-Za-z_ +]+ \([0-9]{4}\) \[imdbId-tt[0-9]{4,12}\]$/
It would probably have to be setup per-directory, because I don't think it would be generic enough to apply without false positives.
During LLM extraction, feed in multiple samples and let the LLM determine if files in that directory can be extracted using a template instead. If they can, it returns the template and that is run instead. If they can't, the LLM extracts it as normal.
dockerizing python is hard
insightface
, which is based on onnx. (ort)[https://github.com/pykeio/ort] in rust might work, but it would require reimplementing a lot of things.doctr
, though results are veeery not so great. paddleocr
might be better but even in python it's a nightmare. There are ports to onnx which could work, but again, it would require reimplementing a load of stuff.A declarative, efficient, and flexible JavaScript library for building user interfaces.
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