[nimsy]

Hi everyone, We have created this visualization of the SAM model that allows you to see the architecture in a interactive manner, along with the code. We made this when trying to implement the SAM model for us to understand it better. Thought I’d share it and some ML folks might find it useful. Please let me know if it did or did not help you! How do you usually go about understanding the model architectures?

https://flowforward.simple.ink/

[arketyp]

I'm working with fine tuning the SAM encoder using LoRA at the moment, so thanks for this. The Segment Anything code on its own, I must say though, is perhaps the most readable and easily navigated DL code I've encountered. Or maybe it's just me coming from mostly a TensorFlow background. I remember I struggled understanding even my own networks when viewing them in TensorBoard. The code peek feature of yours is great.

[nimsy]

Thanks for your comment! Glad it was a (small) help. Yes, Meta research did a great job documenting their code! Quick question: why do you not use Hugging Face with their PEFT library for doing fine-tunning SAM with LoRA?

[arketyp]

The work is based on the SAMed paper and repo, so I'm not re-inventing the wheel, still leveraging best practices. Generally I see a point in keeping things minimal though, anticipating getting gritty with it.

[zorgmonkey]

I like the idea a lot, but I had two main UX problems:

* it is hard to know which of the green blocks can be expanded by clicking, maybe a different color or border for the ones that can be expanded.

* I kept accidentally clicking the text to go to github, but I did realize that if you aim for the edge it works a lot more reliably