Here is a clean, simple, attractive, and professional README for your Stress Detection in IT Professionals project — fully based on your uploaded screenshot, project PDFs, and context from your RAR file.
You can directly paste this into your GitHub repository.
A machine-learning–based system designed to detect stress levels in IT professionals by analyzing facial features using image processing techniques. The system aims to improve employee well-being through live detection, periodic analysis, and personalized recommendations.
This project focuses on identifying stress in IT professionals using advanced ML algorithms and image processing techniques. It is an enhanced version of traditional systems by introducing:
- ✔ Live Stress Detection
- ✔ Periodic Analysis of Users
- ✔ Automated Data Processing
- ✔ Survey-Based Recommendations
- ✔ Admin & User Modules
- ✔ Real-time Image Classification
The goal is to maintain a healthier work environment by monitoring emotional well-being and offering helpful remedies.
- Register & login functionality
- Upload and analyze real-time images
- View stress detection results
- Receive suggestions & stress-relief recommendations
- Manage users
- Review detection logs
- View analytics & system reports
- Face detection
- Stress-level classification
- Feature extraction
- Periodic stress-level monitoring
- HTML
- CSS
- JavaScript
- Python
- Django / Flask (depending on your project structure)
- OpenCV
- scikit-learn / TensorFlow
- NumPy, Pandas
- KNN / SVM / CNN algorithms (based on your documentation)
- MySQL / SQLite
StressDetection/
├── dataset/
├── templates/
├── static/
├── models/
├── app.py / manage.py
├── requirements.txt
└── README.md
- User uploads or captures a facial image
- System preprocesses the image (grayscale, resizing, feature extraction)
- ML model predicts stress level
- User receives results + suggestions
- Admin can monitor analytics and system history
- Clone the repository
git clone https://github.com/your-username/stress-detection.git
cd stress-detection- Install dependencies
pip install -r requirements.txt- Run the application
python app.py- Open in browser:
http://127.0.0.1:5000/
- Add deep learning (CNN) for more accurate results
- Integrate live webcam monitoring
- Deploy as a cloud service
- Add employee wellness dashboard
- Improve model accuracy with larger datasets
Chandra Sekhara Krishna Akash Nutakki AI/ML Enthusiast | Python Developer | Tech Explorer
If you like this project, please consider giving it a ⭐ on GitHub!
If you want, I can also generate:
✅ A professional README badge section
✅ A GIF demo preview
✅ A one-page project explanation for your resume
✅ A LinkedIn project post
Just tell me!