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.