Emotion-Detection-in-Text 😃 🥺 😔

📖 Introduction

Emotion-Detection-in-Text-Hugging-Face is a robust, multilingual sentiment analysis tool powered by Hugging Face Transformers and Gradio. This project enables users to detect emotions in text from various languages by leveraging automatic translation and state-of-the-art NLP models. Whether you want to analyze tweets, comments, or any text data, this project provides an easy-to-use interface and accurate sentiment predictions.

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🚀 Live Demo

Check out the Hugging Face Space:

Vercel Deployment:

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✨ Features

• 🌐 Multilingual Support: Analyze text from multiple languages using automatic translation.
• 🤖 State-of-the-art Model: Utilizes the cardiffnlp/twitter-roberta-base-sentiment model for reliable sentiment analysis.
• ⚡ Fast & Interactive: Gradio-powered web interface for quick and user-friendly predictions.
• 🔌 Easy Integration: Simple Python script for straightforward deployment and customization.
• 🔍 Language Detection: Automatically detects the input language for seamless processing.

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🛠️ Installation

1. Clone the Repository:

   git clone https://github.com/selvaganesh19/Emotion-Detection-in-Text-Hugging-Face.git
   cd Emotion-Detection-in-Text-Hugging-Face
   

2. Create a Virtual Environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use: venv\Scripts\activate
   

3. Install Dependencies:

   pip install -r requirements.txt
   

   If you don't have a requirements.txt, install directly:

   pip install gradio transformers deep-translator langdetect torch
   

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🚀 Usage

1. Start the Gradio App:

   python app.py
   

2. Access the Web Interface:

   • Open your browser and go to the local Gradio link displayed in the terminal (e.g., http://localhost:7860).
   • Enter any text in any supported language.
   • View the predicted sentiment: Positive, Negative, or Neutral.

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🤝 Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create your feature branch (git checkout -b feature/YourFeature).
3. Commit your changes (git commit -am 'Add cool feature').
4. Push to the branch (git push origin feature/YourFeature).
5. Open a Pull Request.

Please see CONTRIBUTING.md for more details.

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📄 License

This project is licensed under the MIT License.

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Developed with ❤️ using Hugging Face Transformers and Gradio.

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Files included:

• app.py - Main application script for sentiment analysis.

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Keywords: NLP, Sentiment Analysis, Multilingual, Hugging Face, Gradio, Emotion Detection, Transformers

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Feel free to open issues for suggestions or bug reports! 🚀

License

This project is licensed under the MIT License.

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🔗 GitHub Repo: https://github.com/selvaganesh19/Emotion-Detection-in-Text-Hugging-Face