Revolutionizing Fly Identification with Artificial Intelligence

FlySpotter Pro is a cutting-edge mobile application designed to transform the way we identify and understand fly species. Leveraging the power of machine learning and cross-platform development, this app provides a seamless, intelligent solution for entomologists, researchers, pest control professionals, and nature enthusiasts.

• Advanced AI Recognition: Utilize state-of-the-art TensorFlow Lite machine learning models to identify fly species with remarkable accuracy
• Instant Results: Get species identification within seconds of capturing or uploading an image
• Continuous Learning: Machine learning model improves with each identification

• Seamless Performance: Native-like experience on both iOS and Android
• Responsive Design: Optimized UI for various screen sizes and devices
• Offline Capability: Full functionality without internet connection

• Secure Authentication:
  • Email/password login
  • Google Sign-In integration
  • Secure Firebase authentication
• Personalized Profiles: Create and customize your user experience
• Data Privacy: Robust protection of user information

• Comprehensive Identification History:
  • Track and review all your previous fly identifications
  • Export and analyze your discovery data
• Interactive Geographical Mapping:
  • Visualize fly species locations on an integrated Google Maps interface
  • Contribute to citizen science by logging fly sightings

• Detailed Species Guide:
  • In-depth information about various fly species
  • Scientific descriptions, habitat information, and interesting facts
• Gamification Elements:
  • Achievements and rewards system
  • Encourage continuous learning and exploration

• Dark Mode: Comfortable viewing in any lighting condition
• Multilingual Support: Accessible to a global audience
• Social Sharing: Share discoveries with the community
• Cloud Synchronization: Seamless data sync across multiple devices

• Flutter: Cross-platform UI framework
• GetX: Efficient state management and dependency injection
• Responsive Widgets: Adaptive design principles

• Firebase:
  • Authentication
  • Firestore real-time database
  • Cloud Storage for images
• TensorFlow Lite: On-device machine learning inference
• Google Maps API: Location services and mapping

• Model: Custom-trained fly species classifier
• Framework: TensorFlow Lite
• Training Data: Comprehensive fly species dataset
• Inference: Fast, efficient on-device predictions

• Flutter: v3.0.0+
• Dart: v2.17.0+
• IDEs:
  • Android Studio
  • Visual Studio Code
  • XCode (for iOS development)

• Android: SDK 21+
• iOS: Version 11+
• Minimum Device Requirements:
  • 2GB RAM
  • 64-bit processor

• Install Flutter SDK
• Set up Firebase project
• Configure Google Maps API key

1. Clone the repository

   git clone https://github.com/KumaloWilson/fly_spotter.git
   cd fly_spotter

2. Install dependencies

   flutter pub get

3. Configure Firebase

   • Add google-services.json (Android)
   • Add GoogleService-Info.plist (iOS)

4. Run the application

   flutter run

Interested in contributing? Great! Please read our CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

This project is licensed under the MIT License - see the LICENSE.md file for details.

• TensorFlow Team
• Flutter Community
• OpenSource Contributors

Encountering issues? Please file a GitHub issue or contact our support team.

Happy Fly Spotting! 🦟🔍