Face Recognition & Attribute Analysis

A real-time AI application capable of identifying people and analyzing their age, gender, and emotion using deep learning models.

✨ Features

• Real-Time Recognition
  • Instant face detection and identification from webcam feed
  • Smooth rendering decoupled from heavy model inference
• Deep Attribute Analysis
  • Age Estimation – Predicts approximate age
  • Gender Detection – Classifies gender with high confidence
  • Emotion Recognition – Detects current facial expression
• Custom Dataset Tools
  • Built-in capture made to easily create training data
  • Automated training pipeline for new faces
• Performance Optimized
  • Multi-threaded architecture for lag-free video
  • Fast Haar Cascade detection + DeepFace accuracy

🛠 Tech Stack

🚀 Getting Started

1. Clone the repository:

   git clone https://github.com/DavitEgoian/deepface-face-recognition-age-gender-emotion.git
   cd deepface-face-recognition-age-gender-emotion

2. Install dependencies:

   pip install deepface opencv-python numpy tf-keras

3. Run the application:

   python face-recog.py

💻 Usage

When the script runs, select an option from the menu:

1. Create Face Dataset

   • Enter a name (e.g., "Alex").
   • The camera will capture 200 images automatically.
   • Images are saved in Dataset/Alex/.

2. Train Face Dataset

   • Processes all images in the Dataset/ folder.
   • Generates embeddings and saves them to embeddings.npy.
   • Run this after adding any new person.

3. Recognize Faces

   • Opens the webcam window.
   • Detects faces and overlays Name, Age, Gender, and Emotion.
   • Press 'q' to quit.

📄 License

This project is licensed under the MIT License.