👉 자랑스럽게 색다른 기꺼이 비주류로 간다. 👈
Fitness App built in Swift / SwiftUI using Core Location, Core Motion, MapKit, Swift Charts, Core Data and Combine
Mac menu-bar app: AirPods posture coaching and head-gesture shortcuts. On-device, no camera, no cloud.
The Application uses CoreMotion and LocationManager to collect the data and saves it to a file that is transferred to the iPhone using WatchConnectivity
Hacking with swift course: 100 days of Swift (UIKit)
In SwiftUI, we use the accelerometer to detect a custom gesture of a user shaking their device in a double shaking motion. Our project represents a clean, modern approach to iOS development and is fun to play with.
SwiftUI sample watchOS app for Watch Ultra that displays depth, pressure, and heart rate metrics.
Gyroscope-driven holographic identity card built with SwiftUI, Core Motion, and Metal.
A modern, SwiftUI-driven demo app suite for collecting iPhone and Apple Watch Core Motion data for ML model training
Minder: a body-doubling focus app for iPhone, two expressive eyes that watch you work, with optional on-device face tracking (Vision). SwiftUI, written on Windows, built and shipped to the App Store entirely by GitHub Actions macOS runners.
A free, open-source iPhone app that turns the phone's built-in sensors into clear live readings — 19 readings, five instruments including your phone in 3D, CSV recording, and no ads, accounts or tracking.
Change slides by swinging an AirPod: a native macOS app and a tiny WebSocket relay for any HTML deck.
macOS menu-bar app that turns AirPods head motion into custom gestures for shortcuts, apps, and window control.
Cross-platform mobile motion gesture recording, replay, and evaluation for iOS and Android.
Track your AirPods head posture and trigger shortcuts with simple head movements.
Kitchen fire prevention app: walk-away detection with Core Motion, escalating haptics, and step-by-step emergency guides. Swift Student Challenge 2026.
An iOS app demo to show list and detail screen of artworks.
AAT Synth is the repository for the first iOS application for Adaptive Art Technologies. It implements an audio engine, as well as a motion controller and a computer vision controller.
Swift watch/iPhone app for motion capture, session transfer, and experimental Core ML feedback. Simulator build verified; 98 Python segmentation tests.
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