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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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AOL buys About.me

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AOL wants to be a cool content company. It recently purchased TechCrunch and Unblab, and today announced its newest acquisition: About.me, a site that lets users create a single, non-interactive profile page that serves as a Web introduction to who they are.  The pages usually contain a name, paragraph about the person, links to  social networks and services, email, and that’s about it. The company also provides some decent analytics about the behavior of those who visit your profile.


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Entity Attribute Value Model

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EAV (Entity-Attribute Value) Model It is a data model to describe entities where number of attributes for the entities could be very large in amount. EAV helps us to overcome the limitations of conventional database model. Ex: Organization ‘ABC’ defines the entity ‘Address’ as: Organization ‘ABC’: Address Line1 Line2 State Country Zip                    At the same time Organization ‘XYZ’ may define ‘Address’ as: Organization ‘XYZ’: Address Line1 Line2 Line3 City State Country Zip Phone A conventional database table design (one fact per column or set of facts per row) is unsuitable for such type of data, because of: ·         the need to continually add new tables or columns whenever new facts need incorporation · ...
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