Featured Post

Efficient Duplicate Image Removal: Using ImageDeDup Python

By -
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...
Post a Comment

VMware Looks To Acquire Novell's SUSE Unit

By -
According to the Wall Street Journal, VMware is attempting to acquire Novell's SUSE Linux operating system business. This move would give VMware a full stack of enterprise software and allow it to establish itself as a full-blown infrastructure and software vendor in direct competition with Red Hat.

Comments

Post a Comment

Let's discuss and learn more

Related Posts

Wikipedia Explains Today's Global Outage

By -
The Wikimedia Tech Blog has a post explaining why many users were unable to reach Wikimedia sites due to DNS resolution failure. The article states, 'Due to an overheating problem in our European data center many of our servers turned off to protect themselves. As this impacted all Wikipedia and other projects access from European users, we were forced to move all user traffic to our Florida cluster, for which we have a standard quick failover procedure in place, that changes our DNS entries. However, shortly after we did this failover switch, it turned out that this failover mechanism was now broken, causing the DNS resolution of Wikimedia sites to stop working globally. This problem was quickly resolved, but unfortunately it may take up to an hour before access is restored for everyone, due to caching effects.
Read More>>  

Opting classic row modeling or EAV data modeling?

By -
Few of the circumstances are listed below where EAV scores over conventional tables: ·          The data type of individual attributes varies. Like in above example EAV is used because the requirements vary from client to client like some may want an extra address like added to existing address format. ·          The categories of data are numerous, growing or fluctuating, but the number of instances (records/rows) within each category is very small. Here, with conventional modeling, the database’s Entity-Relationship Diagram might have hundreds of tables: the tables that contain thousands/ millions of rows/instances are emphasized visually to the same extent as those with very few rows. The latter are candidates for conversion to an EAV representation. Other Related Links: EAV(Entity-Attribute Value) Model EAV versus Row modeling Downsides of EAV data model over class row model Optin...
Read More>>  

Efficient Duplicate Image Removal: Using ImageDeDup Python

By -
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...
Read More>>