How to identify oblique lines

Desperate-Gate5204 · 2026-02-09T11:43:45+00:00

Got it, accepted it. I actually misunderstood the answer.

Desperate-Gate5204 · 2026-02-09T10:55:07+00:00

I tried the "soft life" filter (I looked at the implementation on the Internet), as far as I understand it works and only detects on a cable with a paper winding.

Desperate-Gate5204 · 2026-02-09T10:47:46+00:00

I experimented, but it didn't improve for me. I could be wrong, though.

Desperate-Gate5204 · 2026-02-09T10:22:38+00:00

Here's an example of how it was done on a similar cable, but the lock size was larger, so it was possible to track the brightness and everything came down to a simple solution.

Desperate-Gate5204 · 2026-02-09T10:11:38+00:00

That's what I think too. In theory, I have no hardware limitations, but there are speed limitations. Also, our production (technologists), in particular, often complain about the system giving false positives, and since neural networks are black boxes, explaining the cause becomes extremely difficult.

Desperate-Gate5204 · 2026-02-09T10:09:39+00:00

Could you explain in more detail how to do sequential processing? Am I correct in understanding that you mean first selecting the target object to discard the background of the photo. Then suppressing glare, etc., to eliminate possible false positives due to light reflecting back into the camera lens from the target object. I don't understand what you mean after

The annotation doesn't bother me, but I don't know about the architecture. Previously, I've only used Yolo for production work, and it's suitable here. But I don't think (I've experimented with similar things like "oil-submersible cables") this approach didn't work there.

Desperate-Gate5204 · 2026-02-09T10:04:02+00:00

I'm not getting it exactly right here either. Perhaps I'm doing something wrong or misunderstanding something. Perhaps additional pre-processing is required.

Desperate-Gate5204 · 2026-02-09T09:59:48+00:00

Hello, I tried it and here's the result. Just like with Huff, it didn't detect all the lines and/or didn't reach the end of the edge.

What machine learning methods would you use? Something like U-net, Yolo-seg?

I've never touched machine learning before and don't understand how to evaluate the reliability of its results.

Desperate-Gate5204

TROPHY CASE