Description

This repository contains beginner-friendly Computer Vision projects implemented using Python and OpenCV. The projects cover real-time face detection, motion detection, and basic image processing techniques using images and webcam feeds.

Repository Structure

cv_basics/
│
├── face_detector.py
├── motion_detection.py
│
├── IP/
│   ├── image_processing.ipynb
│   └── doggo.jpeg
│
└── README.md

Projects

Face Detection

Real-time face detection using OpenCV's Haar Cascade Classifier.

Features

• Detects human faces from a live webcam feed
• Uses a pre-trained Haar Cascade model
• Draws bounding boxes around detected faces
• Real-time video processing

Approach

• Capture webcam frames using OpenCV
• Convert frames to grayscale
• Apply Haar Cascade face detection
• Draw rectangles around detected faces
• Display the processed video stream

Output

• Live webcam window
• Face detection in real time
• Bounding boxes around detected faces

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Motion Detection

Real-time motion detection using Background Subtraction (MOG2).

Features

• Detects moving objects in a video stream
• Background subtraction using MOG2
• Noise reduction through image processing
• Contour detection and filtering
• Motion tracking with bounding boxes

Approach

• Capture video frames from webcam
• Apply MOG2 background subtraction
• Generate a foreground mask
• Detect contours from moving regions
• Filter small contours
• Draw bounding boxes around detected motion

Output

• Foreground mask visualization
• Real-time motion tracking
• Bounding boxes around moving objects
• Contour-based object detection

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Image Processing

The IP folder contains experiments demonstrating basic image processing operations using OpenCV.

Files

• image_processing.ipynb – Jupyter Notebook containing image processing examples
• doggo.jpeg – Sample image used for experimentation

Concepts Covered

• Reading and displaying images
• Image resizing
• Cropping
• Color space conversion
• Drawing shapes and text
• Edge detection
• Basic image transformations

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Requirements

Install the required dependencies:

pip install opencv-python numpy

For Jupyter Notebook:

pip install notebook

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Technologies Used

• Python
• OpenCV
• NumPy
• Jupyter Notebook

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Learning Outcomes

This repository demonstrates:

• Real-time video processing
• Face detection using Haar Cascades
• Motion detection using background subtraction
• Contour detection and filtering
• Fundamental image processing techniques
• Practical OpenCV applications