Face Distance Measurement Using OpenCV 🎥📏

This project calculates the distance between a face and the camera in real-time using OpenCV’s Haar Cascade face detector and focal length estimation.

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Features ✨

• Real-time face detection via webcam 👁️‍🗨️
• Calculates camera focal length using a reference image 🎯
• Estimates distance from camera to detected face in centimeters 📐
• Displays distance on live video feed 🖥️

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Requirements 📋

• Python 3.x 🐍
• OpenCV (opencv-python) 🧰
• Webcam 📷
• Reference face image (rf.png) with known face width and distance 🖼️
• Haar Cascade XML file (haarcascade_frontalface_default.xml in data/ directory) 📂

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Installation 🚀

1. Clone or download the repo. 📥

2. Install OpenCV:

pip install opencv-python

3. Download Haar Cascade XML from OpenCV GitHub and put it in the data/ folder. 📂

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Usage ▶️

1. Update the script with your known reference values:

Know_distance = 30          # Known distance (cm) 📏  
Know_width_face = 14.3      # Known real face width (cm) 👤

2. Run the script:

python your_script_name.py

3. Press q to quit. ❌

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How It Works ⚙️

• Calculates the focal length using the known reference distance and face width. 🎯
• Detects faces in the webcam feed. 👁️‍🗨️
• Measures the face width in pixels and estimates distance with the formula:

[ \text{Distance} = \frac{\text{Real Face Width} \times \text{Focal Length}}{\text{Face Width in Image}} ]

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Output Example 📸

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Notes 📝

• Use the same camera for calibration and live detection. 📷
• Adjust Haar Cascade parameters if needed for better face detection. 🔧
• Good lighting improves detection accuracy. 💡

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License 📄

Open source, free to use. 🚀

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