AI Human Emotion Detection System
📌 Project Overview
The AI Human Emotion Detection System is a deep learning application that detects human emotions in real time using a webcam. It uses OpenCV for face detection and a Convolutional Neural Network (CNN) trained on the FER-2013 dataset to classify facial expressions into seven emotions.
🎯 Features
- Real-time webcam emotion detection
- Face detection using OpenCV
- Emotion classification using a CNN model
- Detects seven emotions:
- Angry
- Disgust
- Fear
- Happy
- Neutral
- Sad
- Surprise
- Confidence score display
- MySQL database integration for storing predictions
- Easy-to-use interface
🛠️ Technologies Used
- Python
- TensorFlow / Keras
- OpenCV
- NumPy
- MySQL
- FastAPI (Backend)
- (Frontend)
- Git & GitHub
📂 Project Structure
Emotion-detection/ │ ├── backend/ ├── dataset/ ├── frontend/ ├── model/ │ ├── detect_emotion.py │ ├── train_model.py │ ├── emotion_model.h5 │ ├── db.py │ ├── labels.txt │ └── haarcascade_frontalface_default.xml │ ├── requirements.txt ├── README.md
📊 Dataset
Dataset: FER-2013
The model is trained to classify facial expressions into seven emotion categories using grayscale facial images.
⚙️ Installation
Clone the repository:
git clone https://github.com/hima065/Emotion-Detection.git
Go to the project folder:
cd Emotion-detection
Install the required packages:
pip install -r requirements.txt
Run the application:
python model/detect_emotion.py
📈 Future Enhancements
- User authentication
- Emotion analytics dashboard
- PDF and CSV report generation
- Email notifications
- Cloud deployment
- Mobile application integration