VisionAI - Secure Face Recognition

This repository contains a desktop application for real-time face recognition, age estimation, and emotion detection, built with PySide6 and OpenCV.

Features

• Real-time Recognition: Detects and recognizes faces from a live webcam feed.
• User Management: A graphical user interface to add, update, and delete users for face recognition.
• Model Training: Train the face recognition model with the collected user faces.
• Age and Emotion Detection: Estimates the age and detects the emotion of the person in front of the camera.

Project Structure

opencv_data/      # Datasets, models, and trained data
├── age_model/
├── emotion_model/
└── faces/
main.py           # Main application script
requirements.txt  # Python dependencies
README.md         # Project documentation
...

Getting Started

Prerequisites

• Python 3.x
• OpenCV
• PySide6

Installation

1. Clone the repo:

   git clone https://github.com/Darshan-CodeCrafter/disease-detection.git
   cd disease-detection

2. Install dependencies:

   pip install -r requirements.txt

Running the Application

1. Run the main script:

   python main.py

2. Manage Faces Tab:
   • Add new users by entering a username and selecting an image with a clear face.
   • Train the model using the "Train Model" button. The model status will indicate if it's trained or needs training.
3. Recognize Tab:
   • Click "Start Recognition" to begin detecting and identifying faces from your webcam.

Models Used

• Face Detection: Haar Cascade Classifier.
• Face Recognition: Local Binary Patterns Histograms (LBPH).
• Age Detection: A pre-trained Caffe model.
• Emotion Detection: A pre-trained ONNX model.

Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change.

License

MIT