Image Deduplication and Renaming Script

This script is designed to identify and remove duplicate images in a specified directory based on content similarity, and then rename the remaining images to a standardized format. It uses OpenCV for image processing and the scikit-image library to compare image similarity.

Features

• Traverse a specified directory and list all image files.
• Compare images based on both filename and pixel-wise content.
• Handle different image orientations.
• Remove the lower resolution duplicate when duplicates are found.
• Rename all images to the format image-%timestamp%.%OriginalImageExtension%.
• Perform a sanity check to ensure all images follow the naming convention.
• Log each step of the process to /var/log/dedupe.log.

Requirements

• Python 3.x
• OpenCV
• scikit-image

Setup

1. Install the required libraries:

   pip install opencv-python-headless scikit-image

2. Download the script:

   Save the script to a file, for example, dedupe_and_rename.py.

3. Place the script in /usr/bin directory:

   sudo mv dedupe_and_rename.py /usr/bin/dedupe_and_rename

4. Make the script executable:

   sudo chmod +x /usr/bin/dedupe_and_rename

Usage

Once the script is set up, you can run it from anywhere on your system by calling dedupe_and_rename.

dedupe_and_rename Ensure you update the directory variable in the script with the path to your image directory before running the script.

Logging

** The script logs all its operations to /var/log/dedupe.log. You can check this log file for detailed information about the script's actions and any errors encountered.

Detailed Explanation

list_images(directory, extensions):

** Traverses the directory and lists all image files with the given extensions.

load_image(path):

** Loads an image from the specified file path using OpenCV.

rotate_image(image, angle):

** Rotates an image by the specified angle (0, 90, 180, 270 degrees).

image_similarity(img1, img2):

** Computes the structural similarity index between two images to determine how similar they are.

compare_images_with_orientations(img1, img2):

** Compares images in all orientations to find the highest similarity.

compare_and_remove_duplicates(images):

** Compares each image with every other image in the list, and removes the lower resolution duplicate if they are similar.

generate_unique_filename(directory, file_extension):

** Generates a unique filename using the current timestamp and checks for collisions.

rename_images(directory, extensions):

** Renames all images in the directory to the format image-%timestamp%.%originalImageExtension%.

sanity_check(directory, extensions):

** Ensures all filenames follow the naming convention and handles renaming again if necessary.

Example

Modify the main function in the script to specify your directory:

def main():
    directory = "path/to/your/image/directory"
    extensions = (".png", ".jpg", ".jpeg", ".bmp")
    logging.info(f"Starting duplicate removal in directory: {directory}")
    images = list_images(directory, extensions)
    logging.info(f"Found {len(images)} images to process")
    compare_and_remove_duplicates(images)
    logging.info("Duplicate removal process completed")
    logging.info("Starting renaming process")
    rename_images(directory, extensions)
    logging.info("Renaming process completed")
    logging.info("Starting sanity check process")
    sanity_check(directory, extensions)
    logging.info("Sanity check process completed")

if __name__ == "__main__":
    main()

Replace "path/to/your/image/directory" with the actual path to your directory containing images.