Nervous Detection System
A real-time emotion and nervousness detection system using Streamlit, OpenCV, and deep learning. The app captures video and audio from the user, processes it with machine learning models, and analyzes facial expressions, body cues, and voice stress patterns to detect signs of nervousness.
Features
Live video stream analysis (facial expressions & micro-movements).
Audio stress detection from microphone input.
ML/AI-based prediction for nervousness levels.
Real-time visualization of detection results in the Streamlit UI.
☁️ Easy deployment using Streamlit Cloud.
🛠️ Tech Stack
Frontend: Streamlit
Backend: Python
Computer Vision: OpenCV
Audio Processing: PyAudio / librosa
ML Frameworks: TensorFlow / PyTorch
⚙️ Installation
- Clone the repository
git clone https://github.com//Nervous_detection_system.git cd Nervous_detection_system
- Create virtual environment
python -m venv .venv
- Activate environment
Windows (PowerShell):
.venv\Scripts\Activate.ps1
Linux/Mac:
source .venv/bin/activate
- Install dependencies
pip install -r requirements.txt
▶ Usage
Run the Streamlit app:
streamlit run app.py
Open the link shown in your terminal (usually http://localhost:8501) to start the application.
Demo
