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🧰 C++ OpenCV Toolbox

A growing collection of powerful, hands-on OpenCV examples in modern C++.
This toolbox covers the building blocks of computer vision — from simple image manipulation to real-time detection tasks.

✨ Features

Each mini-project is self-contained and demonstrates a key concept of computer vision:

Project Description
📷 Image Display Load and show images using OpenCV's basic GUI
🔍 Image Resizing Resize images while maintaining aspect ratios
✂️ Image Cropping Extract regions of interest from images
🖍 Annotating Draw shapes and text for image labeling
📐 Warp Perspective Transform angled views into top-down perspectives
🎨 Color Detection (Image) Detect specific colors in still images using HSV filtering
📹 Color Detection (Video) Real-time color detection from webcam or video feed
🧱 Contour Mapping Detect and outline shapes using contours
😀 Face Detection Real-time face detection using Haar cascades
🧾 Document Scanner Detect and straighten a document from a camera frame
🖌 Virtual Paint Track color objects to "paint" on a virtual canvas
🚗 License Plate Detection Identify and isolate vehicle license plates

🧭 Roadmap

✅ Add real-time object tracking

Optical Character Recognition (OCR)

Barcode & QR code detection

Gesture recognition

Deep learning-based object detection (YOLO, SSD)

🔧 Technologies

  • C++17+
  • OpenCV 4.x
  • Visual Studio Code / CMake / vcpkg

📂 Folder Structure

Toolbox/
├── ImageDisplay/
├── ResizeCrop/
├── Annotating/
├── PerspectiveWarp/
├── ColorDetection/
├── ContourMapping/
├── FaceDetection/
├── DocumentScanner/
├── VirtualPaint/
├── LicensePlateDetection/
└── ...

🚀 Getting Started

  1. Clone the repository
    git clone https://github.com/yourusername/CPP-OpenCV-Toolbox.git
    cd CPP-OpenCV-Toolbox
    

💡 Contributing

Got an idea or improvement? Feel free to fork the repo and open a PR!

📝 License

This project is licensed under the MIT License — see the LICENSE file for details.

👋 Author

Bernard Lawes GitHubLinkedIn

About

Object-oriented C++ repo covering the building blocks of computer vision — from simple image manipulation and segmentation, to real-time detection.

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