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camera-streaming

Stream live video and capture JPEG photos from Meta AI glasses in iOS apps.

506|113|Updated Nov 21, 2025
Search Tags:#photo capture#video frames#bandwidth optimization#camera streaming#wearables sdk#iOS swift
One-click install
npx skills add https://github.com/facebook/meta-wearables-dat-ios --skill camera-streaming
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: camera-streaming
Source: https://github.com/facebook/meta-wearables-dat-ios/tree/main/plugins/mwdat-ios/skills/camera-streaming
Command: npx skills add https://github.com/facebook/meta-wearables-dat-ios --skill camera-streaming

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill guides you through streaming live video from Meta AI glasses and capturing still photos reliably, so you can avoid ad-hoc, error-prone camera integration work.

Core Features & Use Cases

  • Camera Stream Setup: Create a device session and add a camera stream with configurable resolution, codec, and frame rate for stable playback.
  • Real-Time Frame Rendering: Subscribe to video frames and convert frames into UI images for a live preview experience.
  • On-Demand Photo Capture: Trigger still-image capture during streaming and handle the resulting photo data for storage or processing.
  • Use Case: Build a hands-free mobile app that streams what the user sees in real time while also capturing JPEG photos for later review, sharing, or analysis.

Quick Start

Set up a DeviceSession, add a Stream using StreamConfiguration, start the stream, listen for video frames to render a preview image, and trigger capturePhoto(format: .jpeg) while subscribing to photoDataPublisher.

Frequently Asked Questions about camera-streaming

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I stream live camera video from Meta AI glasses in an iOS app?▼

You can capture still photos during camera streaming by triggering capturePhoto(format: .jpeg) and subscribing to photoDataPublisher. This handles the resulting photo data for storage, sharing, or analysis during an active streaming session.

How does real-time frame rendering work for wearable camera streaming?▼

Real-time frame rendering works by subscribing to video frame publishers from the active stream. You convert these incoming video frames into UI images to display a live preview experience of what the wearable camera sees.

Can I configure frame rate and resolution for camera streaming on iOS?▼

Yes, you can configure frame rate and resolution for camera streaming by applying supported FPS and resolution options within the StreamConfiguration. Bandwidth-aware constraints are also applied to optimize the streaming performance.

What is the best way to handle bandwidth optimization when streaming video from wearables?▼

The best way to handle bandwidth optimization when streaming video from wearables is to apply bandwidth-aware constraints alongside supported FPS and resolution options in your StreamConfiguration. This ensures stable playback during live video preview.

Do I need to listen to stream state when setting up a camera stream in Swift?▼

Yes, you need to listen to stream state and publishers for video frames and photo data when setting up a camera stream in Swift. Monitoring the stream state ensures the DeviceSession and Stream are started and functioning correctly.

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