JavaCV VS FizzBuzz Enterprise Edition

I'm using https://github.com/bytedeco/javacv/ and trying to set a little server up where I can view the livestream of a camera through the server. I want to try to make a little security camera type project with a raspberry pi. (I know that the library might not work on the pi, but one thing at a time.) If I can get the server working with livestreaming, then I believe I can change any camera library I might end up using.

How is it different from JavaCV?

I'm attempting to make a simple video converter app in Java using JavaCV, i downloaded the Jar files and put them into my repo. this is my current folder structure all of the Jar files are inside the 'libs' folder.

JavaCV to generate the complete mp4 from the rendered frames

I like Java, but if I was doing a pure OpenCV project I would do Python or C++. Anyways, I think looking at examples is the best way to learn. If you use the JavaCV wrapper there are plenty of examples over here https://github.com/bytedeco/javacv/tree/master/samples

Just checking my code. I ended up using this: https://github.com/bytedeco/javacv. Specifically the javacv-platform library: http://bytedeco.org/builds/.

Check this out, this works pefectly inside scala projects so you can do like that: https://github.com/bytedeco/javacv

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I recently wrote a very esoteric Python script. 100 lines of code. No classes, no functions, but yes argparse.

I've tried out the latest open source models on the task. They go bananas. It's like Enterprise fizzbuzz (https://github.com/enterprisequalitycoding/fizzbuzzenterpris...). They love classes and imports and reinventing the wheel. A great way for me to tell trash AI slop code is it'll define a useful constant then 15 lines later do it again with a different name.

They love making code that looks impressive. "Wow look at all the classes and functions. It's so scalable. It's so dynamic. It validates every minutae against multiple schema and solves a problem I never thought about." But it was trash code. One really was 400 lines and it didn't even look like it would work. Can't even imagine what it means for 4.5M moderately good human lines to become what? 27M fluffy filler repeat lines that don't even make sense?

    > https://github.com/EnterpriseQualityCoding/FizzBuzzEnterpriseEdition

> It was a low effort attempt to make something interesting and it wasn’t.

Maybe to you, but others in this thread found it interesting.

> Lowers the bar for what good software really is.

Software is a means to some end, not the end in itself. I can make the best coded software that does nothing [0], there is no point to that other than to practice one's skills, but again, those skills are to achieve something in the end.

[0] https://github.com/EnterpriseQualityCoding/FizzBuzzEnterpris...

https://github.com/EnterpriseQualityCoding/FizzBuzzEnterpris...

I've tried to follow along with it, but man I just can't - it's that crazy.

You need an enterprise FizzBuzz implementation to pass the interview.

https://github.com/EnterpriseQualityCoding/FizzBuzzEnterpris...

To make sure we're really working with Java, look at some short class names:

Java encourages (partly through language design and partly through its community/ecosystem) [Enterprise Grade Programming](https://github.com/EnterpriseQualityCoding/FizzBuzzEnterpris...). The problem isn't the language per se, but that most code bases will require you to earn an architecture astronaut certification for that particular code base.

But also, the Go spec is a couple of pages and the Java spec is, uh, it's taking a while to load for me... ah yes, 876 pages. How's that learning curve?

It gets worse (this isn't too much of an exaggeration): https://github.com/EnterpriseQualityCoding/FizzBuzzEnterpris....

As an undergrad, I once spent about half an hour peer programming with a computer science PhD - it was enlightening.

He didn't have the slightest understanding of software - calling me out for things like not checking that the size of a (standard library) data structure wasn't negative.

Sometimes there's a scary lack of understanding and competency where you'd expect to find it.

Sometimes these things are done for a reason; sometimes it's actually sane and sometimes it's just a way to deal with the lunacy of a codebase forged by the madmen who came before you.