Скачать или смотреть Efficiently Remove Duplicate Images with Python Dictionaries

Discover a simple way to identify and remove duplicate images in Python using a dictionary approach that keeps your primary images intact.
---
This video is based on the question https://stackoverflow.com/q/65686756/ asked by the user 'sar' ( https://stackoverflow.com/u/12957587/ ) and on the answer https://stackoverflow.com/a/65687339/ provided by the user 'Mario Abbruscato' ( https://stackoverflow.com/u/10638652/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Determine Which Duplicate Images to Remove using Python Dictionary

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Efficiently Remove Duplicate Images with Python Dictionaries

When dealing with a large collection of images, duplicate or near-duplicate files can quickly pile up. This not only wastes storage space but also makes it difficult to manage your image library effectively. So how can you systematically identify and delete these duplicate images while keeping the original files? In this guide, we will walk through a practical solution using Python dictionaries.

The Problem

Imagine you have a script that identifies duplicate images based on specific criteria. The duplicates are cataloged in a dictionary where the keys represent the original images, and the associated values contain lists of their duplicates. For instance, in a given dictionary, image0 might map to duplicates 1-5, and you want to delete these duplicates while retaining the first image.

Example Dictionary

Here's a simplified version of what such a dictionary might look like:

[[See Video to Reveal this Text or Code Snippet]]

In this example, the goal is to keep the original image (image0) while deleting duplicates (1-5). Furthermore, we need to ensure that once a duplicate is deleted, it is not considered again.

The Solution

To tackle this problem, we can utilize a Python set to track which images have already been removed. Here’s a step-by-step breakdown of how to implement this:

Step 1: Create a Set for Removed Images

First, we create an empty set called removed. This set will help us record the indexes of images that we have already deleted.

Step 2: Loop Through the Dictionary

We'll use a nested loop to go through each key in the dictionary, and for each key, we will iterate through its associated value list (the duplicates).

Step 3: Check for Existing Deletions

Within the inner loop, we'll check if any duplicates have already been removed by looking them up in the removed set. If an image's index is not in the removed set, we proceed to delete it and add its index to the set.

Step 4: Implement the Deletion Function

Here’s a simple implementation:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

Using a combination of a dictionary to track duplicates and a set to manage deletions allows us to efficiently clean up our image library while keeping the original images intact. Not only does this method streamline the deletion process, but it also ensures that we avoid unnecessary re-checks of already removed images.

Final Thoughts

Managing duplicate images can be a daunting task, especially without a systematic approach. By utilizing Python's data structures, you can develop a robust solution that simplifies this process. Whether you're maintaining a personal collection or managing a large database of images, these techniques can save you time and space.

Remember to tailor the delete_image function according to your specific deletion requirements. Happy coding!