🎯 OpenCV Image Processing

🚀 Learn Computer Vision & Image Processing with OpenCV and Python

A beginner-friendly collection of OpenCV projects covering image processing, transformations, face detection, and face recognition.

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📖 Overview

This repository contains a collection of OpenCV-based image processing and computer vision projects built using Python.

Whether you're just getting started with OpenCV or looking to understand the fundamentals of computer vision, this project provides practical examples covering:

✨ Image Manipulation
✨ Drawing & Annotation
✨ Image Transformations
✨ Face Detection
✨ Face Recognition

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🌟 Features

🖼️ Basic Image Processing

• 📂 Read and display images
• 🎥 Read video streams
• 🔍 Rescale images and frames
• ✏️ Draw shapes and text
• 🎨 Work with colors and pixels

🔄 Image Transformations

• ↔️ Translation
• 🔃 Rotation
• 📏 Resizing
• ✂️ Cropping
• 🪞 Flipping

🤖 Face Detection & Recognition

• 👤 Face Detection using Haar Cascades
• 🧠 Face Recognition using LBPH Recognizer
• 🏋️ Model Training
• 🎯 Face Prediction & Identification

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📂 Project Structure

opencv-image-processing/
│
├── basics/
│   ├── basic.py
│   ├── draw.py
│   ├── read.py
│   ├── rescale.py
│   └── transformations.py
│
├── face_recognition/
│   ├── face_detect.py
│   ├── face_train.py
│   ├── face_recognition.py
│   ├── face_trained.yml
│   ├── features.npy
│   └── labels.npy
│
├── data/
├── media/
├── haar_cascade.xml
├── requirements.txt
├── LICENSE
└── README.md

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🛠️ Installation

1️⃣ Clone the Repository

git clone https://github.com/aimanfazal/opencv-image-processing.git
cd opencv-image-processing

2️⃣ Install Dependencies

pip install -r requirements.txt

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🚀 Getting Started

📷 Reading Images

python basics/read.py

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🎨 Drawing Shapes & Text

python basics/draw.py

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📏 Rescaling Images

python basics/rescale.py

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🔄 Applying Transformations

python basics/transformations.py

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👤 Face Detection

Detect faces using OpenCV's Haar Cascade classifier.

python face_recognition/face_detect.py

Features

✅ Face Localization
✅ Bounding Box Detection
✅ Haar Cascade Classifier

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🏋️ Train Face Recognition Model

Train the face recognition model on your dataset.

python face_recognition/face_train.py

Generated files:

face_trained.yml
features.npy
labels.npy

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🎯 Run Face Recognition

Recognize faces using the trained model.

python face_recognition/face_recognition.py

Recognition Pipeline

Dataset
   ↓
Face Detection
   ↓
Feature Extraction
   ↓
Model Training
   ↓
Face Recognition

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💻 Technologies Used

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🎓 What You'll Learn

By exploring this project, you'll gain hands-on experience with:

• 📸 Image Processing Fundamentals
• 🎨 Image Manipulation Techniques
• 🔍 Face Detection Algorithms
• 🤖 Face Recognition Workflows
• 🧠 OpenCV Machine Learning APIs
• 📊 Computer Vision Concepts

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📌 Future Enhancements

• 🎥 Real-Time Webcam Face Recognition
• 🚗 Object Detection
• 🖌️ Image Filters & Effects
• 🔥 Edge Detection
• 🧠 Deep Learning Face Recognition
• 🖥️ Desktop GUI Application
• 🌐 Web-Based Interface

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🤝 Contributing

Contributions are always welcome!

Steps

# Fork the repository

# Create a new branch
git checkout -b feature-name

# Commit your changes
git commit -m "Add feature"

# Push to GitHub
git push origin feature-name

Then create a Pull Request 🚀

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⭐ Support

If you found this project useful:

🌟 Star the repository
🍴 Fork the project
📢 Share it with others

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📜 License

This project is licensed under the MIT License.

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👨‍💻 Author

Aiman Fazal

❤️ Built with Python & OpenCV

⭐ Don't forget to star the repository if you found it helpful!