Landmark Recognition App

Landmark Recognition App is an Android application that uses a TensorFlow Lite (TFLITE) model to recognize landmarks in real-time through the device's camera. Simply point your camera at a landmark, and the app will provide its name and relevant details.

Features

• Real-time Landmark Recognition: Uses TFLITE model for quick and efficient landmark identification.
• Interactive UI: User-friendly interface for seamless interactions.
• Lightweight and Fast: Designed for optimal performance on Android devices.

How It Works

1. Model: The app integrates a pre-trained TFLITE model for landmark recognition.
2. Camera Access: Captures live camera feed to identify landmarks.
3. Results Display: Recognized landmarks are displayed on the screen with their names and potentially additional information.

Requirements

• Android 8.0 (API level 26) or above
• Camera permissions
• TensorFlow Lite model file (model.tflite)

Installation

1. Clone this repository:

   git clone https://github.com/yourusername/landmark-recognition-app.git

2. Open the project in Android Studio.
3. Sync the project with Gradle files.
4. Build and run the app on an Android device or emulator.

Usage

1. Install and open the app on your Android device.
2. Point your camera at a landmark.
3. The app will display the recognized landmark's name.

Customization

You can replace the default TFLITE model with your own:

1. Place your .tflite model file in the assets folder.
2. Update the model input and output dimensions in the code, if required.

Dependencies

• TensorFlow Lite
• Android CameraX Library
• Glide or Picasso (for image handling, if applicable)

Contributing

Feel free to open issues or submit pull requests to enhance this project.

License

This project is licensed under the MIT License.

Future Improvements

• Integration with external APIs for additional information about landmarks.
• Offline functionality enhancements.
• Expanded landmark database.