I'm also trying to gather a personal backlog of things at home patiently waiting to be resolved, but can't even get myself through the collection phase...
A citizen service initiative that aims to serve as a platform for monitoring areas of need in Puerto Rico.
While I really like it — snappy and encrypted — I was surprised by how much the missing Ultra HDR implementation affects me. Photos are currently uploaded with brightness information but not displayed with it. Therefore, my photos look great in Google Photos but far less vivid in Ente.
For what it's worth, I found a discussion about Ultra HDR. It doesn't seem to be a priority right now, though: https://github.com/ente-io/ente/discussions/779
And for sure, if I get this to a point where it's open-source, I'll post the link here!
A lot of original excellent data processing, statistical analysis, and ML libraries were built into Python and R, so all the deep learning stuff was built on top of those. R is somewhat harder to integrate into a production pipeline due to its typical reliance on something like RStudio, so Python ended up being the de facto standard as it is also well supported in cloud computing environments.
With TensorFlow API's being written for Swift, we might start to see Swift competing with Python.