🎥 Motion Detection Using OpenCV 🕵️‍♂️

This project demonstrates a basic motion detection system using OpenCV and Python. It captures video from a camera, processes the frames to detect moving objects, and highlights detected motion areas in real-time. 🚀

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✨ Features

• 📹 Capture video feed from the webcam.
• 🎨 Convert frames to grayscale and apply Gaussian blur for noise reduction.
• 🔍 Detect motion by comparing the current frame with the first frame.
• 🔲 Highlight moving objects with bounding rectangles.
• 📝 Display status text indicating whether motion is detected.
• ❌ Press q to quit the application.

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🛠️ Requirements

• Python 3.x 🐍
• OpenCV (cv2) 🖼️
• Imutils 🔧
• Time module (standard Python library) ⏰

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📦 Installation

Install required libraries using pip:

pip install opencv-python imutils

▶️ Usage

Run the script to start the motion detection:

python motion_detection.py

⚙️ How It Works

🥇 The first frame is captured and used as a reference.

🖤 Each new frame is converted to grayscale and blurred.

➖ The absolute difference between the current frame and the reference frame is calculated.

⚫ Thresholding and dilation are applied to highlight differences.

🔎 Contours are detected in the thresholded image.

✅ If contours exceed a minimum area, bounding boxes are drawn, and motion is detected.

📺 The video feed with detected motion highlighted is displayed.