🖼️ Image Lab

A modular image processing toolkit with GUI for experimenting with computer vision algorithms and image manipulation techniques.

Image Lab serves as a flexible platform for testing and applying various image processing operations through an intuitive interface, designed for rapid prototyping and iterative development of image analysis workflows.

Preview

🚀 Features

• Modular Processing Pipeline: Extensible architecture for adding new image processing operations
• Real-time Preview: Instant visual feedback for all applied transformations
• Multiple Input Sources: Load images from files, capture screenshots, or use camera devices
• OCR Integration: Built-in text recognition capabilities with configurable parameters
• Configuration Management: Save and load processing presets for reproducible workflows
• Interactive Interface: Tabbed GUI with organized controls for different operation categories

📋 Requirements

• Python: 3.13 or newer
• Operating System: Windows, macOS, Linux
• Dependencies: Managed in pyproject.toml. Note: pytesseract requires Tesseract OCR installed on your system.

📦 Installation

1. Clone the repository

   git clone https://github.com/kodezy/image-lab.git
   cd image-lab

2. Create virtual environment

   python -m venv .venv
   # Windows
   .venv\Scripts\activate
   # macOS/Linuxsource .venv/bin/activate

3. Install the application

   pip install -e .

4. Run the application

   image-lab

⚙️ Configuration

The application uses JSON-based configuration files to store processing presets and settings. All configurations can be saved and loaded through the File menu, enabling reproducible workflows and easy sharing of processing pipelines.

🧪 Usage

1. Load or Capture Image: Import from file, capture screen, or use camera
2. Apply Processing: Configure operations through the tabbed interface
3. Preview Results: View real-time changes in the main display
4. Run OCR (optional): Extract text from processed images
5. Save Results: Export processed images or configuration presets

The modular design allows for easy experimentation with different processing combinations and parameter adjustments.

📁 Project Structure

image-lab/
├── src/ # Source code
│ ├── core/ # Core processing modules
│ ├── gui/ # User interface components
│ ├── infra/ # Infrastructure layer
│ └── config.py # Configuration classes
├── assets/ # Application resources
└── pyproject.toml # Project metadata, dependencies, and CLI

📄 License

MIT License - see LICENSE file for details.