TrainTogether
Fitness coaching · iPhone
An on-device fitness coach with live pose tracking, repetition counting, form scoring, session history, health integration, and local language-model coaching.
Live pose overlay during a squat set: rep count, form score and an "Align knees" correction. App Store screenshot · v2.1
- Role
- Independent Software Engineer
- Timeline
- Nov. 2025 - Present
- Platform
- iOS / iPadOS
- Status
- Released
01
Overview
An iOS and iPadOS fitness coach that performs live pose analysis, repetition counting, form scoring, workout tracking, and on-device coaching.
02
Contributions
- 01
Shipped real-time pose tracking, rep counting, form scoring, HealthKit synchronization, and local session history.
- 02
Built the MediaPipe landmark-to-pose pipeline with per-frame smoothing, rolling-window validation, and body-angle constraints to stabilize counts under real-camera noise.
- 03
Designed FormConfig and RepFormTracker so 32+ exercise detectors share one scoring and feedback path.
- 04
Integrated llama.cpp coaching, SQLite persistence, optional CloudKit backup, and deterministic mock-landmark tests.
03
System design
- Capture and pose
- Camera frames are converted into normalized MediaPipe landmarks and filtered before exercise evaluation.
- Exercise logic
- Exercise-specific detectors plug into shared rep-state, scoring, and feedback abstractions.
- Local intelligence
- llama.cpp provides coaching on device after model installation, reducing network dependency.
- Platform services
- HealthKit, CloudKit, local databases, and Apple UI frameworks connect the analysis engine to the complete product.
04
Outcome
A production fitness workflow in which the core analysis path remains local, testable, and reusable across a growing exercise catalogue.
Core stack
- SwiftUI
- MediaPipe
- llama.cpp
- SQLite
- CloudKit
- HealthKit
Discuss the work
Need implementation detail or engineering context?
Email a specific question about the architecture, trade-offs, or validation approach.
