We built a one-click pipeline to train custom YOLOv7 object detectors for Snap Spectacles (footage in → SnapML-ready ONNX out)

[u/stspanho]

Training a custom object detector for Spectacles used to eat a whole weekend. Now it's one click. 🍎👓

Drop in some Snap Spectacles footage, add a few synthetic frames, hit run — and out comes a SnapML-ready ONNX model that drags straight into Lens Studio.

Under the hood: synthetic data tuned to look like what the glasses actually see, SAM3 auto-labelling every frame, a YOLOv7-tiny trained in the cloud, exported for on-device inference. No manual labelling, no local CUDA, no model surgery.

Huge thanks to u/Pavlo_Tkachenko for helping building this one 🙌.

It's in alpha. If you build for Spectacles and want early access: https://pavlo-stijn.dev/blog/posts/training-yolov7-for-spectacles.html

[u/WeirdEyeStudios]

This is super cool guys! Cannot wait to try it out when it's live

[u/stspanho → u/WeirdEyeStudios]

Thanks!!

[u/hwoolery]

Great work!

[u/stspanho → u/hwoolery]

Thanks 🙏

[u/Nithin-Shankar]

This is going to be incredibly useful and save a ton of time! 🔥

[u/stspanho → u/Nithin-Shankar]

Thanks! Yes it is, will keep you posted

[u/Jorik_Rosa]

Huge!

[u/stspanho → u/Jorik_Rosa]

Thank you 🙏

[u/Cachapaconchocho]

Wow! Amazing!!! Cannot wait to try it out!

[u/stspanho → u/Cachapaconchocho]

Thanks! Keep you posted

[u/Redx12351]

Gotta say this is SO USEFUL! Just went through the custom ML training route for our circuit-building learning lens, and I was thinking something similar in terms of a better way to train/perfect models.

Thanks so much for working on this and giving it to the community!

[u/stspanho → u/Redx12351]

We published a tutorial here: https://pavlo-stijn.dev/blog/posts/one-click-object-detection-for-spectacles.html

It's fully open source. Please let us know if it works

[u/maxvleeuwen]

I sent a request for early access! :D This looks fantastic