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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.