Text to Emotion Detection is a project that aims to classify the emotions expressed in text messages or documents. It utilizes machine learning techniques to predict the dominant emotion associated with a given piece of text.
Installation To use this project, follow these steps:
Clone the repository: git clone https://github.com/codewithrishav/text-to-emotion-detection.git Install the required dependencies: pip install -r requirements.txt Usage Open the terminal and navigate to the project directory. Run the text_to_emotion.py script: python text_to_emotion.py Enter the text you want to analyze when prompted. The program will classify the emotion and display the results. Example:
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$ python text_to_emotion.py Enter the text: I'm so excited for the weekend! Emotion: Joy Features Classifies text into one of the following emotions: Joy, Sadness, Anger, Fear, Surprise, Disgust, Neutral. Provides accurate and reliable emotion predictions based on machine learning models trained on labeled data. Handles both short text messages and longer documents. Contributing We welcome contributions from the community! If you want to contribute to this project, please follow these steps:
Fork the repository. Create a new branch: git checkout -b feature/your-feature Make your changes and commit them: git commit -m 'Add your feature' Push the changes to your forked repository: git push origin feature/your-feature Open a pull request and describe the changes you've made. Please refer to our Contribution Guidelines for more details.
License This project is licensed under the MIT License.
Acknowledgments We would like to thank the developers of the XYZ library for their contribution to this project.
Contact If you have any questions or suggestions, please feel free to reach out to us at rishav098kumar@gmail.com.
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