👁️ Computer Vision Face Detection and Recognition System

A Python-based application utilizing OpenCV and deep learning techniques to perform real-time face detection and recognition. This project demonstrates the implementation of computer vision algorithms to identify and verify individuals from live video feeds or static images.

---

---

🚀 Features

• 🎥 Real-time Face Detection – Using Haar cascades and deep models
• 🧠 Face Recognition – Verifies identities by comparing faces against a known database
• 🖼️ Image and Video Support – Works on static files and live webcam streams
• 🖱️ Graphical Interface – Tkinter-based UI for interaction
• 📁 Scalable Face Database – Organize new identities easily
• 🧩 Modular Codebase – Clean, organized Python scripts for detection, recognition, and GUI

---

🛠️ Technologies Used

Component	Technology
Programming Language	Python 3.x
Computer Vision Library	OpenCV
Deep Learning Framework	TensorFlow/Keras
GUI Framework	Tkinter
Data Storage	Local filesystem (for images), SQLite (optional)
Version Control	Git & GitHub (if used for sharing)

---

▶️ How to Use

Follow these steps to run the project via the provided Jupyter Notebook.

💻 Prerequisites

• Python 3.x
• Jupyter Notebook (Install: pip install notebook)
• Required libraries: OpenCV, TensorFlow, Keras, Pillow

  pip install opencv-python tensorflow keras pillow

📦 Step 1: Download the Project

Clone the repository or download the ZIP file and extract it.

📸 Step 2: Prepare the Data Directory

Before running notebook cells, organize your data directory as follows:

data/
├── Alice/
│   ├── 1.jpg
│   └── 2.jpg
└── Bob/
    ├── 1.jpg
    └── 2.jpg

• Each folder (Alice, Bob, etc.) should contain clear, front-facing images (2–5 images per person).

---

🚀 Step 3: Run the Jupyter Notebook

1. Open your terminal and navigate to the project directory.
2. Launch Jupyter Notebook:

jupyter notebook

3. In your browser, open the notebook file (faceDetection.ipynb) and run cells sequentially.

---

🧯 Troubleshooting

• Module Not Found? Ensure you've installed dependencies:

pip install opencv-python tensorflow keras pillow notebook

• Notebook not opening? Ensure Jupyter is correctly installed and running.

---

🙌 Acknowledgments

• OpenCV – For providing an incredibly powerful open-source computer vision library.
• TensorFlow & Keras – For simplifying deep learning model development and training.
• Stack Overflow & GitHub Community – For helpful discussions and code references during development.
• Tutorial Authors & Online Resources – For inspiration and foundational guidance in face recognition techniques.
• Everyone Testing the System – For helping refine the interface and improve accuracy with real-world feedback.