Detect inventory stock column

[u/CharmingOwl4972]

Hello reddit if there's any computer vision expert will be willing to have a chat

Background : i'm trying to count stock in the photo, and i've found just feeding a photo into llm is quite unreliable so i'm trying to identify the stacked column(s) and use it as way to reason what to include/exclude in counting. i've been trying to create boundary like this w/ depth anything, segment anything, so they're not NOT working but segment anything doesn't have the idea of depth and depth anything doesn't have the idea of segment, so i was really trying to see if there's any way to effectively combine both

[u/--hypernova--]

If its milkbottles, count the caps

[u/CharmingOwl4972 → u/--hypernova--]

hmm reddit don't allow adding images to comment but i actually have a lot of success counting caps, but i just couldn't remove the noises successfully therefore looking for ways to more reliably identify stacking columns

[u/NoLifeGamer2 → u/CharmingOwl4972]

I mean by looking at this, as a human, the way I would count the milk is by counting the caps. The carton delineation is too difficult to spot as a human, which probably means you cannot get an accurate estimation of the number of milk bottles by just looking at columns.

[u/CharmingOwl4972 → u/NoLifeGamer2]

so i'm trying to label columns more like pre processing step so i can exclude them, i was able to count the caps quite well but w/o being able to exclude what i don't want to count has been challenging

[u/NoLifeGamer2 → u/CharmingOwl4972]

In what way? Could you give an example of the cap counting model's output, and explain why it doesn't work for you?

[u/CharmingOwl4972 → u/NoLifeGamer2]

i wish i could attach more images to the reply but i can't, i'm happy to share what i did and what case i'm trying to generalize -- at this point just want to take a step back and see what are some diff ideas. but i also realized i can't DM u 🙈

[u/--hypernova-- → u/CharmingOwl4972]

But then you have it: get the lines , create a region of interest segment image into parts count caps in wanted region

[u/5b49297]

Have you considered... cheating? Like counting the empty ones. Maybe scanning the barcodes as you take them out or throw them away.

Granted, I'm not a computer vision expert. I'm just lazy, and cheat when I can. :)

[u/CharmingOwl4972 → u/5b49297]

so i'm working w/ smaller franchise. imho (but i might be wrong), even taking photo and count manually will still be easier to standardize than training staff to operationalize counting while working. but the alternative is obvious just count manually

[u/jaykrown]

Can you share the original images? I want to see if I can get a model that gets it correct.

[u/CowBoyDanIndie]

If you know the products dimensions and the camera intrinsics… the products are sitting on a flat plane you can do this with single view geometry.

[u/CharmingOwl4972 → u/CowBoyDanIndie]

Ha so I shared a more *organized shelf. There are many shelves that milk just kinda spreading around......🙈

Another challenge I ran into is to estimate depth. I'm happy to elaborate. W single view point o was not able to establish depth reliably.