Face Detection with OpenCV

A simple face detection project built using OpenCV’s Haar Cascades.
This is a practical implementation I built after completing courses on OpenCV.

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🧠 Motivation & Background

While studying OpenCV, I learned about object detection, cascades, and image processing pipelines.
To solidify my understanding, I decided to build a hands-on face detection project that:

• Detects faces in real time (via webcam)
• Draws bounding boxes around detected faces
• Is light-weight and easy to extend

This project is a result of applying theory in code and experimenting with parameters and detection accuracy.

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🗂️ Project Structure

• face_detect.py — main Python script that captures video and performs face detection
• haarcascade_frontalface_default.xml — pre-trained cascade file used by OpenCV
• sample_images/ — (optional) some test images you used
• README.md — this documentation

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🚀 Getting Started

Prerequisites

You’ll need:

• Python (3.6+ recommended)
• OpenCV library for Python
• (Optional) imutils or numpy if you used them

You can install dependencies with:

pip install opencv-python
# If using extra libs:
pip install numpy imutils
python face_detect.py