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Efficient Duplicate Image Removal: Using ImageDeDup Python

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Efficient Duplicate Image Removal: A Python Guide In this blog post, we will walk you through the process of identifying and removing duplicate images from your directories using Python. We will leverage perceptual hashing to find similar images and delete duplicates while keeping the largest file in the group. This solution is perfect for users who want to save disk space and keep their image collections organized. Why You Should Use This Code Over time, especially when dealing with large collections of images, duplicate files can accumulate. These duplicates take up unnecessary space on your system. Manually sifting through these images can be tedious, but with the help of Python, perceptual hashing, and concurrent processing, this task becomes much easier. Benefits: Efficient Duplicate Detection : By using perceptual hashing (PHash), the code compares images based on their v...
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EAV versus Row modeling

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Following are main features/downsides EAV has over classic row modeling technique.
  • A row-modeled table is homogeneous. It will always carry same type of data in contrast to EAV modeled table where this cannot be an issue.
  • The data type of the value column/s in a row-modeled table is pre-determined by the nature of the facts it records. In contrast, in an EAV table, the conceptual data type of a value in a particular row depends on the attribute in that row.
  • A Row modeling technique data increase only in one direction i.e. from Upside-down whereas in EAV data model data increase in both directions i.e. from upside down as well as from left-right.







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