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Let’s play rock, paper scissors.You think of your move and I’ll make mine below this line in 1…2…and 3. I choose ROCK. Well? …who won. It doesn’t matter cause you probably glanced at the word “ROCK” before thinking about a move or maybe you didn’t pay any heed to my feeble attempt at playing rock, paper, scissor with you in a blog post. So why am I making some miserable attempts trying to play this
Did you know that you can actually stream a Live Video wirelessly from your phone’s camera to OpenCV’s cv2.VideoCapture() function in your PC and do all sorts of image processing on the spot? Cool huh? In today’s post not only we will do just that but we will also build a robust Intruder Detection surveillance system on top of that, this will record video samples whenever someone enters your room and will also send you
In the previous tutorial we learned how the DNN module in OpenCV works, we went into a lot of details regarding different aspects of the module including where to get the models, how to configure them, etc.  This Tutorial will build on top of the previous one so if you haven’t read the previous post then you can read that here.  Today’s post is the second tutorial in our brand new 3 part Deep Learning
In this tutorial we will go over OpenCV’s DNN module in detail, I plan to cover various important details of the DNN module that is never discussed, things that usually trip of people like, selecting preprocessing params correctly and designing pre and postprocessing pipelines for different models. This post is the first of 3 in our brand new Deep Learning with OpenCV series. All three posts are titled as: Deep Learning with OpenCV DNN Module,
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This tutorial will serve as a crash course to dlib library. Dlib is another powerful computer vision library out there. It is not as extensive as OpenCV but still, there is a lot you can do with it.This crash course assumes you’re somewhat familiar with OpenCV, if not then I’ve also published a crash course on OpenCV too. Make sure to download Dlib Resource Guide above which includes all important links in this post. Side

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