PixClassifier

PixClassifier is a minimalist tool for classifying images based on their quality, size, and noise levels. The tool provides both a graphical user interface (GUI) and support for advanced image processing.

Features

• Image Quality Classification: Categorizes images into high, medium, or low quality based on resolution and DPI.
• Size Classification: Classifies images into small, medium, or large size categories.
• Noise Analysis: Identifies high, medium, or low noise levels using Laplacian variance.
• Real-time Progress: Updates the progress bar as images are processed.
• Folder Management: Removes empty folders automatically after processing.

Installation

Prerequisites

• Python 3.8 or later
• Required libraries:
  • Pillow
  • opencv-python
  • tkinter (comes pre-installed with Python on most systems)

Install Dependencies

Run the following command to install the required dependencies:

pip install Pillow opencv-python

Usage

GUI Mode

1. Run the script:

   python PixClassifier.py

2. Select input and output folders using the GUI.
3. Click Start Processing to classify images. The progress bar will update as processing completes.

Output

Images are organized into categorized folders in the output directory:

output_folder/
├── High_Quality/
├── Medium_Quality/
├── Low_Quality/
├── Small_Size/
├── Medium_Size/
├── Large_Size/
├── High_Noise/
├── Medium_Noise/
└── Low_Noise/

Example

Drag and drop your images into the input folder and watch as they are sorted based on quality, size, and noise.

Icon

License

This project is open source and available under the GPL v3.