python-imagesearch | wrapper around opencv2 and pyautogui to do image | Computer Vision library

Trio won't directly parallelize CPU-bound code like this. Being an "async framework" means that it just uses a single CPU thread, while parallelizing I/O and networking operations. If you insert some calls to await trio.sleep(0) then that will let Trio interleave the image searching with other tasks, but it won't make the image searching any faster.

What you might want to do, though, is use a separate thread. I guess your code is probably spending most of its time in opencv, and opencv probably drops the GIL? So using threads will probably let you run your code across multiple CPUs at once, while also letting other async tasks run at the same time. To manage threads like this, Trio lets you do await trio.to_thread.run_sync(some_sync_function, *args), which runs some_sync_function(*args) in a thread. If you run multiple calls like this simultaneously in a nursery, then you'll use multiple threads.

There is one major gotcha to watch out for with threads, though: once a trio.to_thread.run_sync call starts, it can't be cancelled, so timeouts etc. won't take effect until after the call finishes. To work around this you might want to make sure that individual calls don't block for too long.

Also, a side note on style: functions made for Trio usually don't take timeout= arguments like that, because if the user wants to add a timeout, they can write the with block themselves around your function just as easily as passing an argument. So this way you don't have to clutter up APIs with timeout arguments everywhere.