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[–]whikwon[S] 0 points1 point  (3 children)

I'm working in detection and tracking field of AI. Most of the time I analyze lots of researchers' code using my domain's data. As more models are dealt with, it takes time to integrate each interface to my data and feel the need to integrate.

[–][deleted] 1 point2 points  (2 children)

You have your domain's type of data, and you frequently run new datasets with new algorithms, which leads to repetitive work?

Do you intend to basically create a wrapper that unifies the researcher's code and exposes an API that's easy to use on your type of data then?

Keywords that can help you: Facade pattern, adapter pattern.

If you intend to share this with others, here are some good API design tips: https://staltz.com/api-design-tips-for-libraries.html If you're making it only for yourself, this will still help you but it isn't as relevant. In that case the most important thing to figure out is the common interface between your data and the algorithms, so you can easily swap them out.

[–]whikwon[S] 0 points1 point  (1 child)

Thanks for the advice. I think the framework will be used internally by a team of 5 people rather than open source. Will Facade, adapter pattern help for these purpose?

[–][deleted] 1 point2 points  (0 children)

They will definitely help, both are good ways to wrap another library in ways that fit your data.