{"id":32907361,"url":"https://github.com/cbonello/ml_vision","last_synced_at":"2026-07-02T10:31:29.653Z","repository":{"id":320811073,"uuid":"1082911941","full_name":"cbonello/ml_vision","owner":"cbonello","description":"A Flutter application that uses Google ML Kit to detect and classify objects in photos captured with the device camera.","archived":false,"fork":false,"pushed_at":"2025-10-26T01:43:28.000Z","size":278,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-10-26T03:28:37.090Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Dart","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cbonello.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-10-25T01:25:15.000Z","updated_at":"2025-10-26T01:43:31.000Z","dependencies_parsed_at":"2025-10-26T03:28:48.932Z","dependency_job_id":"f9426d07-2e46-4093-853f-2b3eb5d7bb05","html_url":"https://github.com/cbonello/ml_vision","commit_stats":null,"previous_names":["cbonello/ml_vision"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/cbonello/ml_vision","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbonello%2Fml_vision","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbonello%2Fml_vision/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbonello%2Fml_vision/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbonello%2Fml_vision/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cbonello","download_url":"https://codeload.github.com/cbonello/ml_vision/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbonello%2Fml_vision/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35043933,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-07-02T02:00:06.368Z","response_time":173,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-11-10T15:32:07.222Z","updated_at":"2026-07-02T10:31:29.645Z","avatar_url":"https://github.com/cbonello.png","language":"Dart","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ML Vision - Object Detection App\n\nA Flutter application that uses Google ML Kit to detect and classify objects in photos captured with the device camera. Built for iOS 15.5+ and Android, this app demonstrates powerful on-device machine learning capabilities.\n\n## Features\n\n- **Camera Integration**: Tap the camera button to capture photos using the device camera\n- **Real-time Object Detection**: Leverages Google ML Kit for accurate object detection and classification\n- **Visual Bounding Boxes**: Displays color-coded boxes around detected objects in the image\n- **Interactive Selection**: Tap any detected object card to highlight its corresponding bounding box\n- **Detailed Results**: Displays detected objects with:\n  - Primary object label with highest confidence\n  - Multiple classification possibilities per object\n  - Confidence scores (percentage)\n  - Visual confidence indicators (HIGH/MEDIUM/LOW)\n  - Color-coded badges\n  - Bounding box coordinates\n- **Adjustable Settings**: Configure detection parameters:\n  - Confidence threshold slider (adjust sensitivity)\n  - Image quality control\n- **Split-Screen Layout**: Fixed image display at top with scrollable object list below\n- **Clean UI**: Modern Material Design 3 interface\n- **On-device Processing**: All detection happens locally using Google's ML Kit\n- **Multi-label Classification**: Shows alternative classifications for each detected object\n\n## Requirements\n\n- **iOS**: 15.5 or later (compatible with iOS 26)\n- **Android**: API Level 21 or later\n- **Xcode**: 13.0 or later (for iOS development)\n- **Flutter**: 3.9.2 or later\n- **CocoaPods**: Latest version (for iOS)\n\n## Technologies Used\n\n- **Flutter**: Cross-platform framework\n- **Google ML Kit**: On-device machine learning for object detection and image labeling\n- **Packages**:\n  - [`google_mlkit_object_detection`](https://pub.dev/packages/google_mlkit_object_detection) ^0.15.0 - Google ML Kit object detection\n  - [`google_mlkit_image_labeling`](https://pub.dev/packages/google_mlkit_image_labeling) ^0.14.1 - Google ML Kit image labeling\n  - [`image_picker`](https://pub.dev/packages/image_picker) ^1.1.2 - Camera and photo library access\n\n## Getting Started\n\n### 1. Clone and Setup\n\n```bash\ncd ml_vision\nflutter pub get\n```\n\n### 2. Install iOS Dependencies\n\n```bash\ncd ios\npod install\ncd ..\n```\n\n### 3. Run the App\n\nConnect your iOS device or start the iOS simulator:\n\n```bash\nflutter run\n```\n\nOr open in Xcode:\n\n```bash\nopen ios/Runner.xcworkspace\n```\n\n## iOS Configuration\n\nThe project includes all necessary iOS configurations:\n\n### Deployment Target\n- Set to iOS 15.5 in both `Podfile` and Xcode project settings\n\n### Permissions\nThe following permissions are configured in `Info.plist`:\n\n- `NSCameraUsageDescription`: Camera access for taking photos\n- `NSPhotoLibraryUsageDescription`: Photo library access for image selection\n\n### Bundle Identifier\n- `com.example.mlVision`\n\n## How to Use\n\n1. **Launch the app** on your iOS device\n2. **Tap the camera button** (floating action button) to open the camera\n3. **Take a picture** of objects you want to detect\n4. **View results** showing:\n   - Captured image\n   - List of detected objects\n   - Confidence scores for each detection\n\n## Project Structure\n\n```\nlib/\n└── main.dart              # Main app with object detection logic\n\nios/\n├── Podfile                # CocoaPods dependencies (iOS 15.5)\n├── Runner.xcodeproj/      # Xcode project\n└── Runner/\n    └── Info.plist         # iOS permissions and configuration\n```\n\n## Troubleshooting\n\n### ML Kit dependencies not found\n\nRun:\n```bash\nflutter clean\nflutter pub get\ncd ios\npod install\ncd ..\n```\n\n### Building for iOS-13.0 error\n\nEnsure the deployment target is set to iOS 15.5:\n- Check `ios/Podfile`: `platform :ios, '15.5'`\n- Check Xcode project settings: Target → Deployment Info → iOS 15.5\n\n### No objects detected\n\nML Kit works best with:\n- Clear, well-lit images\n- Distinct objects with defined shapes\n- Common everyday objects (furniture, food, animals, vehicles, etc.)\n- Objects that aren't too small in the frame\n\n### Camera not working\n\nVerify camera permissions are granted in device Settings → Your App → Camera\n\n## Known Limitations\n\n- Requires physical device with camera for best results\n- Object detection accuracy depends on Google ML Kit models\n- Detection works best with common objects in well-lit conditions\n- May not detect very small objects or unusual items\n\n## License\n\nThis project is a demonstration application for educational purposes.\n\n## Acknowledgments\n\n- Built with [Flutter](https://flutter.dev/)\n- Uses [Google ML Kit](https://developers.google.com/ml-kit)\n- Object detection via [google_mlkit_object_detection](https://pub.dev/packages/google_mlkit_object_detection) package\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcbonello%2Fml_vision","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcbonello%2Fml_vision","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcbonello%2Fml_vision/lists"}