Emotion-Detector-by-Python

An Emotion Detector in Python is a program that analyzes data (typically text, images, or audio) to classify or infer emotions expressed in the input. This is accomplished by leveraging Natural Language Processing (NLP), Computer Vision, or Audio Signal Processing techniques, often combined with machine learning or deep learning models. Features

• Text-Based Emotion Detection:

  • Analyzes written text for emotional sentiment using NLP techniques.
  • Supports multi-class emotion classification (e.g., happy, sad, angry, neutral).

• Facial Emotion Recognition:

  • Detects emotions by analyzing facial expressions in images or real-time video feeds.
  • Uses pre-trained deep learning models for accurate detection.

• Audio Emotion Analysis:

  • Processes speech or audio signals to infer emotions.
  • Extracts features like pitch, tone, and intensity for classification.

• Hybrid Emotion Detection:

  • Combines text, facial, and audio analysis for multi-modal emotion recognition.

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Technologies Used

• Programming Language: Python
• Libraries and Tools:
  • NLP: NLTK, TextBlob, spaCy, Transformers
  • Computer Vision: OpenCV, dlib, FER, DeepFace
  • Audio Analysis: librosa, pyAudioAnalysis
  • Machine Learning Frameworks: TensorFlow, PyTorch, scikit-learn
  • Visualization: Matplotlib, Seaborn

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Installation

1. Clone the Repository:

   git clone https://github.com/yourusername/emotion-detector.git
   cd emotion-detector

Install Dependencies: Use pip to install the required libraries:

bash Copy code pip install -r requirements.txt Download Pre-Trained Models (if applicable): Follow instructions to download any pre-trained models required for facial or text analysis.

Usage

1. Text-Based Emotion Detection Run the script for text analysis:

bash Copy code python text_emotion.py --input "Your text here" 2. Facial Emotion Recognition Run the facial emotion detection script for images:

bash Copy code python face_emotion.py --image_path "path/to/image.jpg" 3. Audio Emotion Analysis Analyze emotions in an audio file:

bash Copy code python audio_emotion.py --audio_path "path/to/audio.wav" 4. Real-Time Emotion Detection Enable real-time emotion recognition via webcam:

bash Copy code python real_time_emotion.py Project Structure bash Copy code emotion-detector/ ├── models/ # Pre-trained models ├── data/ # Sample datasets ├── scripts/ # Core analysis scripts ├── requirements.txt # Required libraries ├── README.md # Project documentation └── LICENSE # License file Examples Facial Emotion Detection:

Text Emotion Analysis: vbnet Copy code Input: "I am thrilled about the event!" Output: Emotion detected: Happy Future Enhancements Multi-modal emotion detection combining text, audio, and image data. Support for additional emotion classes. Integration with a web-based interface for real-time analysis. Contributing Contributions are welcome! Please create a pull request or open an issue for any feature suggestions or bug reports.

License This project is licensed under the MIT License.