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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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Flash Comes To the iPad Via RipCode

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Texas-based company RipCode has announced a new 'clientless Flash video codec' that will allow Flash content to be streamed on Apple's iPad. This would include sites like Hulu and YouTube, assuming the respective companies don't find a way to block it. According to RipCode's press release, the TransAct Transcoder V6 captures the iPad's request for Flash content and converts it into a special format that the device accepts and plays. This is all done without a local client or user intervention. 'RipCode's Transactional Transcoding platform enables an alternate and immediate solution to this issue, opening up video content to users without requiring the content hoster to move to HTML5 or pre-transcode entire video libraries from Flash to an iPad-accepted container format. By transcoding the content "in the cloud," it is essentially analogous to a network-based Flash to MP4 or MPEG-TS video adaption layer.

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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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