u/Beneficial_Pace_3535

I’ve been experimenting with Meta Display Glasses recently. Apps for the glasses can be built as web apps, so naturally I wondered: could Flutter Web run on them?

I wasn’t sure it would work well. Flutter Web isn’t exactly lightweight, and the glasses are quite a different target from a regular browser.

After playing with the build and a few configurations, I got it working.

Nothing fancy yet, just the default Flutter counter app. But it runs directly on the glasses display: the Flutter UI is rendered in front of you, and interacting with the controls updates the counter as you’d expect from the same app running in a browser.

What I find more interesting is the potential for existing Flutter apps.

If you wanted to add a companion experience for Display Glasses, you could potentially keep it in the same codebase and reuse your existing logic, models, networking, and some widgets, while building a UI specifically for the glasses.

I have a few things I want to try next. Curious what other Flutter devs would experiment with on a display like this!

Meta opened up the Ray-Ban camera feed to third-party mobile apps through the Wearables Device Access Toolkit (DAT). There are official SDKs for iOS and Android but nothing for Flutter, so I wrote the bridge.

flutter_meta_wearables_dat covers the whole lifecycle: registration through the Meta AI app, permissions, device state, live streaming, photo capture.
One more case where Flutter just pays off: one codebase, one setup, and you skip juggling two native SDKs that don't behave the same way.

The frame pipeline was the interesting part. Pushing decoded frames over a method channel dies at 24-30fps, so the native side registers them as a Flutter texture instead. You just render Texture(textureId: ...) and the frames never cross the platform channel. Raw pixels are still available on a separate stream when you need them.

That stream is also where the privacy question gets decided, and I know a lot of people are uneasy about these glasses for good reason. Pairing the feed with something like ML Kit means the analysis runs entirely on the phone: text recognition, object detection, face detection, all local. No frame ever leaves the device, nothing hits a server. Worth knowing that building on this doesn't have to mean streaming what someone sees to the cloud.

No glasses on your desk? There's an optional add-on that simulates a paired pair using your phone's camera.

One honest caveat: DAT is still developer preview, so you can build and ship to testers but public App Store and Play Store releases are limited to select Meta partners for now.

pub.dev: https://pub.dev/packages/flutter_meta_wearables_dat
GitHub: https://github.com/rodcone/flutter_meta_wearables_dat

Issues and PRs welcome!