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CoreLabs · Experiment / PROJECT

LiveTether

A new webcam connection for a camera left behind.

Publicly available · macOS 14.1+

Chapters 4Topics 6
PROJECT STORY
01 / 04
LiveTether app icon
MACOS

Connect the camera again.

Panasonic’s LUMIX Webcam Software does not support macOS 14.1 and later. CoreLabs built and released LiveTether as a small experiment in macOS camera connectivity. It takes the live view from a USB-tethering-capable LUMIX and makes it available to FaceTime, QuickTime, OBS, and other camera apps. The setup guide walks through allowing the camera extension and connecting in PC (Tether) mode. LiveTether is an independent project, unaffiliated with Panasonic.

MACOS

Framing that follows people.

Choose the live-view size, adjust Auto Framing, and inspect frame statistics. Auto Framing finds people and smoothly follows a head-and-shoulders or upper-body crop. Vision analyzes a small grayscale image locally on the Mac; images are neither stored nor sent elsewhere. This capture shows settings before a camera is connected. USB delivers a compressed live view: selecting 1080p output does not increase its source quality.

The controls you need, close at hand.

Menu bar

Check connection status and reach Auto Framing, settings, and the setup guide.

General

Install, reinstall, or remove the camera extension, and choose whether to open the app at login.

Advanced

Manage camera USB product IDs. If a camera is not detected, find its ID in System Information and add it here.

From USB live view to a macOS camera.

The menu bar app uses Swift 6.2, Xcode 26, and SwiftUI. XcodeGen defines the project, while the local LumixKit Swift package separates PTP messages, connection and reconnection, camera discovery, video processing, and communication with the extension.

ImageCaptureCore discovers the USB camera and opens a PTP session. While a camera app is using it, LiveTether fetches and decodes JPEG frames at up to 30 fps and passes them to a CoreMediaIO camera extension. Live view stops when unused. Output formats are 1920×1080, 1280×720, and 1280×960, with letterboxing where aspect ratios differ.

Auto Framing combines Vision person and face detection with CoreVideo and Accelerate processing. The project includes unit tests for connection and video logic, a synthetic camera-extension probe, and a video-file framing probe. Localization keys and window layouts are checked in English, Korean, and Japanese.

Installer packages are distributed through GitHub Releases; the build tools support app signing and installer notarization. The app requires macOS 14.1 or later and a LUMIX camera with USB tethering support. The repository documents compatibility and setup, including HDMI capture as an alternative when full camera video quality is required.

  • Swift 6.2
  • SwiftUI
  • ImageCaptureCore
  • CoreMediaIO
  • Vision
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