🧠 PyQt5 Image Processing Studio

A modular and object-oriented image processing application built with PyQt5, designed for real-time image operations such as grayscale and HSV conversion, segmentation (Multi-Otsu, Chan-Vese, Morphological Snakes), and edge detection (Sobel, Scharr, Prewitt, Roberts).

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🚀 Features

• 🎨 Real-time image display and manipulation
• 🧩 Modular architecture using object-oriented design (OOP)
• 📚 Inheritance, Polymorphism, Encapsulation, Abstraction applied throughout
• ⚙️ Dynamic threshold slider for edge detection
• ♻️ Undo/Redo operation history
• 📦 Integrated file handling and export features
• 🌈 Smooth UI transitions using fade and hover animations
• 🧵 Multithreaded processing via QThread to ensure responsive GUI
• 🧪 Doxygen-style comments for all modules (documentation-ready)

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🧱 Project Structure

📁 root/
├── main.py                      # Main application runner
├── LabFinal.py                 # Auto-generated GUI class from Qt Designer
├── conversion.py               # RGBToGray, RGBToHSV + Handler
├── segmentation.py             # MultiOtsu, Chan-Vese, MorphSnakes + Handler
├── edge_detection.py           # Sobel, Scharr, etc. + EdgeDetectionHandler
├── file_operations.py          # File save/export dialogs
├── image_manager.py            # Image load, clear, UI display updates
├── processing_worker.py        # QThread-based image processor
├── ui_state_manager.py         # GUI button/state control
├── ui_effects.py               # Fade & hover animations
├── style.qss                   # External style sheet
├── icons/                      # Custom icons for UI
└── README.md                   # You're here!

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📷 Image Operations

Operation Type	Methods
Conversion	Grayscale, HSV
Segmentation	Multi-Otsu, Chan-Vese, Morph. Snakes
Edge Detection	Sobel, Scharr, Prewitt, Roberts

All operations are encapsulated in handler classes, enabling runtime polymorphism and abstraction.

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🧠 Object-Oriented Design (OOP)

Each operation type is defined using:

• ✅ Abstract Base Classes (ABC)
• ✅ Specific subclasses implementing .apply() or .detect()
• ✅ Handler classes to isolate operation logic

Example:

class ImageOperation(ABC):
    def apply(self): pass

class RGBToGray(ImageOperation):
    def apply(self):
        # grayscale conversion logic

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💻 How to Run

1. Make sure you have Python 3.7+ installed.
2. Install dependencies:

pip install PyQt5 scikit-image numpy

3. Run the application:

python main.py

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📚 Requirements

• PyQt5
• scikit-image
• numpy

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📖 Documentation

All modules are documented using Doxygen-style Python docstrings. You can generate HTML or PDF documentation using Doxygen with the following config:

doxygen -g  # (first time only)
# edit Doxyfile to include *.py and set EXTRACT_ALL = YES
doxygen Doxyfile

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✨ Screenshots

🖼️ Main Interface

🔍 Segmentation Example

🧠 Edge Detection Result

🎨 Hue Saturation Result

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👨‍💻 Author

Doğukan Avcı
Eskişehir Osmangazi University - Electrical & Electronics Engineering

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📝 License

This project is open for academic, educational, and personal use. Contact the author for other use cases.

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✪️ Acknowledgements

• PyQt5 Team
• scikit-image contributors
• Qt Designer GUI Toolkit

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