opencv-rust VS Ray

https://github.com/twistedfall/opencv-rust makes it evident that they do try to support using a prebuild system-opencv. Maybe it is not correctly recognized?

opencv

The de facto solution for smart image processing is to use a computer vision library, such as opencv, which has experimental rust bindings: https://github.com/twistedfall/opencv-rust

There is an OpenCV bindings crate. This example might be what you're after https://github.com/twistedfall/opencv-rust/blob/master/examples/video_capture.rs

For example, this is the build script of the opencv bindings: https://github.com/twistedfall/opencv-rust/blob/master/build.rs

I’m trying to get around a known build issue—it would be great for it to be fixed upstream, but I don’t have any control over it except for setting OUT_DIR during its compilation.

I've been using https://github.com/twistedfall/opencv-rust a lot lately and it's really fantastic, they've done a great job matching up with how C++ works, so there are definitely good examples out there.

I never tried it, but the OpenCV bindings might work.

I thought it was going to be unsafe because of how Mat is implemented (more information here). ... I tested it and it should be fine memory-wise. My thought was that the code below was going to be allowed to compile.

22. Ray | Github | tutorial

Training times for GSM8k are mentioned here: https://github.com/ray-project/ray/tree/master/doc/source/te...

Here's a reference from RLlib that points to docs and an example, and here's one from one of my projects that includes all my own implementations

RLlib

⦿ AWS Glue Data Quality - Automatic data quality rule recommendations based on your data AWS Glue for Ray - Data integration with Ray (ray.io), a popular new open-source compute framework that helps you scale Python workloads

https://ray.io (just dropping the link)

I've wondered whether it's easier to add data analyst stuff to Elixir that Python seems to have, or add features to Python that Erlang (and by extension Elixir) provides out of the box.

By what I can see, if you want multiprocessing on Python in an easier way (let's say running async), you have to use something like ray core[0], then if you want multiple machines you need redis(?). Elixir/Erlang supports this out of the box.

Explorer[1] is an interesting approach, where it uses Rust via Rustler (Elixir library to call Rust code) and uses Polars as its dataframe library. I think Rustler needs to be reworked for this usecase, as it can be slow to return data. I made initial improvements which drastically improves encoding (https://github.com/elixir-nx/explorer/pull/282 and https://github.com/elixir-nx/explorer/pull/286, tldr 20+ seconds down to 3).

[0] https://github.com/ray-project/ray

Adding these for anyone who had a similar question about Ray vs dask 1, 2, 3