🎥 Face Detector (OpenCV + Python)

Real-time face detection with FPS counter, timestamp overlay, and dynamic face-count styling.

✨ Project Overview

This project is a clean, real-time face detection app built with OpenCV. It captures frames from your webcam, converts them to grayscale for efficient processing, detects faces using Haar Cascades, and overlays useful UI elements: a live face counter, timestamp, and a frames-per-second (FPS) indicator. Rectangle colors change dynamically based on the number of faces detected (🟩 green ≤ 2, 🟥 red ≥ 3) for instant visual feedback.

🌟 Features

• Real-time webcam capture (VideoCapture)
• Haar Cascade face detection (haarcascade_frontalface_default.xml)
• Dynamic rectangle color based on face count
• On-screen overlays: face count, timestamp, FPS
• Simple keyboard control: press q to quit

🧰 Tech Stack

• Python 3.8+
• OpenCV (opencv-python)

🚀 Getting Started

1) Prerequisites

• Python 3.8 or newer
• Webcam access

2) Installation

pip install opencv-python
  

The Haar Cascade file is resolved via OpenCV’s built-in path: cv2.data.haarcascades + "haarcascade_frontalface_default.xml"

3) Run

python main.py
  

🕹️ Controls

• q — Quit the app

🧪 Troubleshooting

• Black window / no camera: ensure your webcam is connected and not used by another app.
• Slow FPS: close other heavy apps; reduce waitKey delay or resize frames before processing.
• No faces detected: check lighting, camera angle, and that the Haar Cascade path resolves correctly.

🗺️ Roadmap

• 🎯 Add eye/Smile detection
• 🕶️ Fun overlays (sunglasses/emoji)
• 💾 Snapshot capture (s to save)
• ⚙️ CLI flags for camera index and cascade params

🤝 Contributing

Issues and PRs are welcome! Please open an issue to discuss major changes.