Image Color Classifier

This Python script efficiently classifies images based on their average color and organizes them into color-specific folders. It supports a variety of image formats, including raw files.

Features

• Color Classification: Determines the average color of each image by computing the mean of its RGB channels.
• Organized Sorting: Categorizes images into "red," "green," and "blue" folders based on their predominant color.
• Format Compatibility: Supports common image formats (.jpg, .jpeg, .png, .gif) and various raw file formats (.arw, .cr2, .nef, .dng).

Dependencies

• rawpy: Used for reading and processing raw image files.
• PIL (Pillow): Handles image processing for non-raw formats.
• NumPy: Enables efficient numerical operations for array manipulations.

Usage

1. Clone Repository:

   git clone https://github.com/your-username/image-color-classifier.git

2. Navigate to Project Folder

   cd image-color-classifier

3. Install Dependencies

   pip install rawpy pillow numpy

4. Run the Script

   python image_classifier.py

5. Specify Input Folder Replace the input_folder variable with the path to your local image folder in the script.

Example

• Consider running the script on a folder containing a mix of JPEG, PNG, and RAW image files. The script will create subfolders ('red', 'green', 'blue') and organize images based on their predominant color.

  python image_classifier.py
  

Contributing

• Contributions are welcome! Feel free to open issues, submit feature requests, or create pull requests to enhance the functionality of the script.