[mgradowski]

That's a nice and tidy codebase, real pleasure to read.

> I believe many (most?) opencv & numpy operations release the GIL.

Any idea how I can determine this? I am prototyping a real time machine vision application targeting 2x720p@240fps and I want to avoid writing any C++ for as long as possible.

[drothlis]

I don't know much about Python's C API, but this is the line in the OpenCV Python bindings that drops the GIL: https://github.com/opencv/opencv/blob/4.5.0/modules/python/s...

(see https://docs.python.org/3/c-api/init.html#releasing-the-gil-... in the Python C API manual).

That's only called from the ERRWRAP2 macro here: https://github.com/opencv/opencv/blob/4.5.0/modules/python/s...

That macro, in turn, is called from gen_template_func_body in gen2.py: https://github.com/opencv/opencv/blob/4.5.0/modules/python/s...

And that seems to be a code generator that is generating the bindings for all the OpenCV functions: https://github.com/opencv/opencv/blob/4.5.0/modules/python/s...

As to testing this, on Linux I'd run `atop` to see if your program is using all available CPUs.

[mgradowski]

Nice spelunking! If there is hope of avoiding C++ altogether, then I'll try testing it again on something beefier than my laptop. Thanks for taking the time and effort.