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Live Emotion Detection Flutter Project

Overview

This Flutter project is designed to perform real-time emotion detection using computer vision and machine learning. It can identify emotions like happiness, sadness, anger, and more from live camera feed or images.

Features

  • Real-time emotion detection using the device's camera.
  • Support for various emotions like happiness, sadness, anger, and more.
  • User-friendly interface with live emotion feedback.

Prerequisites

Before you begin, ensure you have met the following requirements:

  • Flutter installed on your development machine.
  • A compatible Android or iOS device or emulator for testing.

Getting Started

To get started with this project, follow these steps:

  1. Clone this repository to your local machine:

    git clone https://github.com/your-username/emotion-detection-flutter.git
  2. Navigate to the project directory:

    cd emotion-detection-flutter
  3. Install dependencies:

    flutter pub get
  4. Run the app:

    flutter run

Usage

  • Open the app on your device or emulator.
  • Grant camera permissions when prompted.
  • Point the camera at a face, and the app will detect and display the detected emotion in real-time.

Technology Stack

  • Flutter: The UI framework used for building the mobile app.
  • TensorFlow Lite: For running the machine learning model for emotion detection.
  • Camera Plugin: For accessing the device's camera.

Contributing

Contributions are welcome! If you'd like to contribute to this project, please follow these steps:

  1. Fork the repository.
  2. Create a new branch for your feature: git checkout -b feature-name.
  3. Make your changes and commit them: git commit -m 'Add some feature'.
  4. Push to the branch: git push origin feature-name.
  5. Create a pull request.

Acknowledgments

  • This project was inspired by the idea of using AI for emotion detection in real-time applications.
  • Special thanks to the open-source community for providing resources and libraries.

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