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Tono + YOLO iOS App Integration Checklist

This document outlines the step-by-step process for integrating the functionality of the Tono app into the YOLO iOS app framework.

Phase 1: Project Setup and Analysis

  • Create a backup of both projects

    • Create a backup of the original Tono app
    • Create a backup of the original YOLO iOS app

  • Analyze both codebases thoroughly

    • Document the architecture of Tono (SwiftUI-based)
      • SwiftUI-based UI with TabView navigation
      • Core Data for persistence
      • ARKit for object recognition
      • AVFoundation for audio recording and playback
      • SpeechManager for text-to-speech
      • PronunciationAPI for pronunciation feedback
    • Document the architecture of YOLO iOS app (UIKit-based)
      • UIKit with Storyboards for UI
      • AVFoundation for camera access
      • Vision and CoreML for object detection
      • UIKit-based visualization of detection results
    • Identify shared components and potential integration points
      • Camera and video processing
      • Object detection pipeline
      • UI components that need to be merged

  • Set up a new branch for integration work

    • Create a new branch from the YOLO iOS app repository (created 'tono-integration' branch)
    • Ensure all YOLO models are properly included (verified models in YOLO/Models directory)

Phase 2: Core Functionality Migration

  • Integrate Core Data model from Tono

    • Copy the Tono.xcdatamodeld to the YOLO project
    • Create a Persistence.swift file in YOLO project based on Tono's implementation
    • Add the TaggedObject entity and related methods
    • Test Core Data functionality in the YOLO app

  • Implement language learning utilities

    • Create a Utilities folder in the YOLO project
    • Add SpeechManager.swift for text-to-speech functionality
    • Add PronunciationAPI.swift for pronunciation assessment
    • Add TranslationManager.swift for object translations
    • Test each utility independently

  • Modify YOLO object detection to support language learning

    • Create a translation database (JSON or plist) with English-Chinese-Pinyin mappings for COCO classes
    • Modify the YOLO detection pipeline in ViewController.swift to include translations
    • Add methods to look up translations for detected objects
    • Test detection with translations

Phase 3: UI Integration

  • Decide on UI framework approach

    • Option 1: Keep UIKit base and integrate SwiftUI views using UIHostingController ✓
      • This approach minimizes changes to the YOLO detection pipeline
      • Allows reuse of Tono's SwiftUI views with minimal modifications
      • Requires bridging between UIKit and SwiftUI

  • Implement tab-based navigation

    • Create a custom UITabBarController in the YOLO app
    • Set up the first tab with the existing YOLO ViewController
    • Create UIHostingControllers for SwiftUI-based tabs:
      • CollectionViewController (hosting CollectionView)
      • PracticeViewController (hosting PracticeView)
      • SettingsViewController (hosting SettingsView)
    • Implement tab switching logic

  • Implement detection popup

    • Create a SwiftUI overlay view for detected objects
    • Implement a UIHostingController to present the overlay
    • Add translation display to the popup
    • Add pronunciation recording and feedback UI
    • Ensure proper layout in both portrait and landscape orientations

Phase 4: Feature Implementation

  • Collection Feature

    • Implement the CollectionView as a SwiftUI view
    • Create a UIHostingController to present it in the UIKit app
    • Add functionality to save detected objects to Core Data
    • Implement filtering and sorting capabilities
    • Test saving and retrieving objects

  • Practice Feature

    • Implement the PracticeView with its sub-components:
      • FlashcardView for flashcard practice (placeholder implemented)
      • QuizView for quiz-based learning (placeholder implemented)
      • PronunciationPracticeView for pronunciation practice (placeholder implemented)
    • Create a UIHostingController to present it in the UIKit app
    • Ensure practice features work with collected objects
    • Test all practice modes

  • Settings Feature

    • Implement the SettingsView as a SwiftUI view
    • Create a UIHostingController to present it in the UIKit app
    • Integrate YOLO's existing settings (model selection, confidence threshold)
    • Add Tono's language settings (API key, language selection)
    • Test settings persistence

Phase 5: Audio and Speech Integration

  • Implement audio recording functionality

    • Set up AVAudioRecorder for pronunciation practice
    • Implement proper audio session management
    • Add audio playback capabilities
    • Test recording and playback

  • Implement text-to-speech

    • Integrate SpeechManager for Chinese pronunciation
    • Ensure proper pronunciation of Chinese characters
    • Add controls for speech rate and volume
    • Test text-to-speech functionality

  • Implement pronunciation feedback

    • Integrate the PronunciationAPI
    • Implement visual feedback for pronunciation accuracy
    • Add gamification elements for pronunciation practice
    • Test pronunciation feedback

Phase 6: Testing and Refinement

  • Test object detection performance

    • Ensure YOLO detection still works efficiently
    • Test with various lighting conditions and scenarios
    • Optimize for performance if needed
    • Compare detection speed before and after integration

  • Test language learning features

    • Verify all language learning features work correctly
    • Test pronunciation feedback accuracy
    • Ensure Core Data persistence works properly
    • Test with various Chinese characters and phrases

  • UI/UX testing

    • Test on different iOS devices and screen sizes
    • Ensure proper layout in both orientations
    • Verify accessibility features
    • Test tab navigation and transitions

Phase 7: Finalization

  • Code cleanup and optimization

    • Remove any redundant or unused code
    • Optimize performance bottlenecks
    • Ensure code follows consistent style guidelines
    • Add proper error handling

  • Documentation

    • Update README and documentation
    • Document the integration process and architecture
    • Add comments to code for future maintenance
    • Create user guide for new features

  • Prepare for distribution

    • Update app icons and launch screen
    • Configure proper app permissions
    • Prepare for App Store submission if applicable
    • Test app signing and distribution

Technical Considerations

Architecture Decisions

  • The YOLO app uses UIKit with Storyboards while Tono uses SwiftUI
  • We'll use UIHostingController to embed SwiftUI views in UIKit
  • Core Data integration will require careful planning for model versioning
  • We'll keep the YOLO detection pipeline intact and extend it with translation capabilities

Performance Considerations

  • YOLO object detection is computationally intensive
  • Adding language features should not significantly impact detection performance
  • Consider background processing for non-critical tasks like pronunciation assessment
  • Optimize Core Data queries for large collections

Dependencies

  • Ensure all required dependencies from both apps are properly integrated
  • Resolve any dependency conflicts
  • Consider using Swift Package Manager for managing dependencies
  • Minimize third-party dependencies to reduce maintenance burden

iOS Version Support

  • YOLO requires iOS 17.0+ for trained models
  • Ensure all features are compatible with iOS 17.0+
  • Test on multiple iOS versions if possible
  • Document minimum iOS version requirements