Kalman VS rapidobj

Since you mentioned C++ and Kalman filters, I author this Kalman filter library which helped me to get reacquainted to control theory, tries to be approachable, and lists a variety of sources to ease in the topic with examples.

Yes, and here's one for sanitizers. Other tools, documentation, and coverage in the neigbhorong files.

I've been learning FectContent as well with some successes and failures.

My goal with this Kalman filter for C++ is to solve your exact question.

I released a first version of a generic Kalman filter.

I use fmt and others in my project with CMake fetch and it's been a good experience so far: fetch, declare, link in a few lines. Hope this can be useful to someome.

Gratuitous French codebase self-promotion though. /s

Would you be open to exploring an implementation collaboration? I author a C++ Kalman library and would like to expand demonstrators.

A façade (example) included only for your GCC builds and with the fmt library would allow you to generically use the std::format support in your code. Avoiding the fmt:: and dependencies with MSVC. When the support lands in GCC, only that file would need to be deleted.

I use it with boilerplate similar to this: https://github.com/FrancoisCarouge/Kalman/blob/develop/benchmark/benchmark.cpp and run the executables with priority and pining: nice -n 20 tasker -- cpu-list 0

I wrote a rapidobj library for parsing Wavefront .obj files. It's an old text format for 3D data. This library was optimised to quickly process large files (see benchmarks); it can parse millions and even tens of millions of triangles per second.

I just released rapidobj v1.0. It's a fast .obj file parser. May be useful to those who need to quickly load large .obj models (of course, you will still need to transform the data into something that's GPU friendly). Third party benchmarks: https://aras-p.info/blog/2022/05/14/comparing-obj-parse-libraries/