Image Equalizer GUI

A desktop application for enhancing image contrast using histogram equalization, built with Python and Tkinter. The project provides a simple interface to load an image, adjust quantization settings, and compare the original and equalized results visually.

Overview

This repository contains a graphical tool for experimenting with image enhancement techniques. It uses a histogram-based equalization approach to improve brightness and contrast, making details in low-contrast images easier to interpret.

The interface allows users to:

• Import an image from disk
• View the processed output in a resizable canvas
• Adjust quantization parameters in real time
• Switch between original, equalized, histogram, and comparison views
• Save generated histogram outputs in the data/ directory

Features

• Image import and display
• Histogram equalization for contrast enhancement
• Adjustable quantization level
• Side-by-side comparison visualization
• Histogram plotting for analysis
• Clean dark-themed desktop UI
• Built with Python and common scientific imaging libraries

Tech Stack

• Python 3
• Tkinter / CustomTkinter
• ttkThemes
• NumPy
• Pillow (PIL)
• scikit-image
• Matplotlib
• Pandas

Repository Structure

image_equalizer_GUI/
├── data/                     # Generated output images and supporting files
├── src/
│   ├── histogram.py          # Histogram-related utilities
│   ├── imageWidget.py        # Canvas/image display widgets
│   ├── interface.py          # Main application entry point
│   ├── menu.py               # UI controls and options menu
│   ├── panels.py             # Interface panels and layout helpers
│   ├── settings.py           # Configuration settings
│   ├── tools.py              # Core image processing functions
│   └── __pycache__/          # Python bytecode cache
├── README.md                 # Project overview and usage instructions
└── .gitignore                # Ignore generated files and local environment state

Installation

1. Clone the repository:

git clone https://github.com/VelascoRt/image_equalizer_GUI.git
cd image_equalizer_GUI

2. Create and activate a virtual environment (optional but recommended):

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

3. Install dependencies:

pip install numpy pandas pillow matplotlib scikit-image customtkinter ttkthemes

Running the Application

From the repository root, start the GUI with:

python src/interface.py

Or run it from the src directory:

cd src
python interface.py

How It Works

The application reads an image, converts it to grayscale when needed, applies quantization, and uses a histogram equalization procedure to redistribute intensity values. The processing pipeline includes:

• Image loading
• Intensity normalization
• Histogram computation
• Cumulative probability transformation
• Result rendering in the GUI

This makes it useful for improving contrast in images that are too dark, washed out, or difficult to interpret visually.

Usage Notes

• Use the interface controls to select the image view mode.
• Change the quantization value to tune the equalization strength.
• Compare the original image with the equalized output to evaluate the enhancement.
• Generated histogram visualizations are stored under the data/ folder.

License

MIT License

Contributing

Contributions are welcome. If you want to improve the GUI, optimize the processing logic, or add new image tools, feel free to open a pull request with a clear description of the changes.

Author

VelascoRt