I put together a YOLO tune for climbing hold detection a while back (trained on 10k labels) and this is 90% as good out of the box - just misses some foot chips and low contrast wood holds, and can't handle as many instances. It would've saved me a huge amount of manual annotation though.

[Update: should have mentioned I got the 4 second from the roboflow.com links in this thread]

That used SAM 2, and in my experience SAM 2 was more or less perfect—I didn’t really see the need for a SAM 3. Maybe it could have been better at segmenting without input.

But the new text prompt input seams nice; much easier to automate stuff using text input.

SAM3 seems to less precisely trace the images — it'll discard kids drawing out the lines a bit, which is okay, but then it also seems to struggle around sharp corners and includes a bit of the white page that I'd like cut out.

Of course, SAM3 is significantly more powerful in that it does much more than simply cut out images. It seems to be able to identify what these kids' drawings represent. That's very impressive, AI models are typically trained on photos and adult illustrations — they struggle with children's drawings. So I could perhaps still use this for identifying content, giving kids more freedom to draw what they like, but then unprompted attach appropriate behavior to their drawings in-game.

[1] https://chat.vlm.run

[2] https://vlm.run/orion

* Does Adobe have their version of this for use within Photoshop, with all of the new AI features they're releasing? Or are they using this behind the scenes? * If so, how does this compare? * What's the best-in-class segmentation model on the market?

Is there some functionality I'm missing? I've tried Safari and Firefox.