It took about a week before
I was happy with it.
There is a reason that Alan Turing invented program verification in the 1940s [1].
Let me finish with a quote from computing pioneer M. Wilkes [2]: "I well remember when this realization first came on me with full force. The EDSAC was on the top floor of the building and the tape-punching and editing equipment one floor below. [...] It was on one of my journeys between the EDSAC room and the punching equipment that "hesitating at the angles of stairs" the realization came over me with full force that a good part of the remainder of my life was going to be spent in finding errors in my own programs."
[1] A. M. Turing, Checking a Large Routine. http://www.turingarchive.org/browse.php/b/8
[2] M. Wilkes, Memoirs of a Computer Pioneer, MIT Press, 1985, p. 145.
I don't think you can reasonably expect software that extracts features from photographs to be proven correct. What would the specification even look like? How many man years would you spend on verifying OpenCV and the two dozen other dependencies you rely on? It's not like all math papers provide machine checked proofs and that would probably be an easier endeavor.
Then when you edit any parts of the code and the test suite breaks - you can see that some of the invariants had been broken.
This is even more important for python, as at least having a simple test suite can already tell whether your environment is sane. And that's about 90% of the newcomer's time saved.
Researchers aren't paid (and usually aren't trained) to write software that can be installed on more than one computer. I don't like that situation either, but that how it currently is. Research code also suffers from accelerated bit rot. The dependencies are often research code themselves and projects are abandoned when the results are published.