🎨 OOP Image Processing Application

A modular Object-Oriented Image Processing Desktop Application built with Python and Tkinter.

This project demonstrates:

• Clean OOP Architecture
• Factory Design Pattern
• Modular Filter System
• GUI Component Separation
• Extensible Design

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🚀 Features

🖼 Image Operations

• Load image (JPG, PNG, BMP, TIFF, GIF)
• Apply filters:
  • Blur
  • Sharpen
  • Grayscale
  • Edge Detect
  • Sepia
  • Invert
• Reset to original
• Save processed image

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🏗 Architecture

Core Components

• ana_uygulama.py → Main GUI controller
• resim_yonetici.py → Image state & processing manager
• fabrikalar.py → Factory Pattern implementation
• filtreler.py → Filter classes
• gui_components.py → UI components
• logger.py → Logging system

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🔄 Processing Flow

1. User selects image
2. ImageManager loads original image
3. User selects filter
4. Factory creates filter object
5. ImageManager applies filter
6. Processed image updates in UI

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🖼 Screenshots

Blur Filter

Sharpen Filter

Grayscale Filter

Edge Detection

Sepia Filter

⚙ Installation

python -m venv .venv
# Windows
.venv\Scripts\activate
pip install -r gereksinimler.txt

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▶ Run

python ana.py

or

python ana_uygulama.py

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📂 Project Structure

otobus_terminali/
│
├── ana.py
├── ana_uygulama.py
├── config.py
├── temel_siniflar.py
├── resim_yonetici.py
├── fabrikalar.py
├── filtreler.py
├── gelistirmeler.py
├── gui_components.py
├── logger.py
├── utils.py
├── gereksinimler.txt
├── testler/
├── screenshots/
└── README.md

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➕ How to Add a New Filter

1. Create new class in filtreler.py
2. Implement process() method
3. Register filter inside fabrikalar.py
4. Add button/menu connection

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🧠 Technologies Used

• Python
• Tkinter
• Pillow (PIL)
• OpenCV
• OOP Principles
• Factory Pattern

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📜 License

MIT License