Optical Chracter Recognition on Super market bills

This was a problem I was working for a while. It is to do a proof of concept and see, with how much accuracy we can recognize a supermarket receipt. The scope is to try with 2 major supermarkets. One is Tesco and the other one is Sainsbury which are two of the leading supermarkets in the UK. The data set had over 2000 images and was a very challenging data set. Almost 60% for the receipts had below 20-30% accuracy (bad lighting conditions/angles/low resolution/crumpled) when the receipts are processed through the Tesseract OCR.

  1. Okay, Now let’s start with a reasonable receipt. This receipt is readable for the human eye. Let see how the Tesseract reads this. (Hmm Not bad at-least we can get the supermarket name, less than 5% accuracy)


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A GPU Based Real Time People Re-identification Inside a Came Network

This article is about our final year project which dates back to 2015 AD, to re-identify people inside a camera network. Basically at the end of the day if you point a person in the CCTV and ask where did that person go it will generate a video of the person wandering around.

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Okays not as worse as the sponge bob re-identification. But yea it works.  And yes the system runs real time too.

The following video shows the system running. That’s a very long video I would suggest to keep on reading. 😀

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Going Reactive with play frame work

Reactive programming is where the program reacts to events. With the popularity of event-driven, scalable, and real-time interactive architectures the concept of “reactiveness” is increasingly gaining attention. The concept is growing in importance in the Java domain in recent years as Netflix has created its RxJava library and Lightbend has created its Akka middleware stack.

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