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Comment by boredemployee | Hacker News Reader

How can I learn the practical side of computer vision in 2026?

I'm not interested in understanding papers or the math behind it, but rather in how to put a system into production, whether it's object detection, running 20 cameras in parallel on a single computer, like sizing hardware for a specific task, and so on.

Any tips?

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By doing it. Decide on a small project, like tracking your cat, detecting food items in your fridge, then take it step by step.

Then do a slightly more ambitious project. Start with something very simple.

It also heavily depends on what you already know regarding programming, image processing etc.

Just start cooking , python is easy and the bindings are not that hard

Try a coding agent for writing and tuning the OpenCV part, and have it explain its choices. That's probably the most practical path to shipping a working system.

Speaking from experience: never used OpenCV before, recently vibe coded a tool that makes supercuts of pool videos, trimming each clip from the cue ball's first strike to when the motion stops.

One of the great things about OpenCV is how ubiquitous it is, there's a ton samples online and well represented in frontier model training data. I recently vibe-coded an object detector for my own personal photo library so I could separate out my pictures with humans in them. Very approachable with Codex + feeding it a sample from Github.

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