Artificial Intelligence

Hey guys and welcome back, so in this little demo that you are seeing right now is an app that is demonstrating how YOLOv4 can be used for social distancing. So, in this tutorial, I am going to show you how you can implement your own social distancing app using YOLOv4. So how the app works is that after we perform detection with YOLOv4, we calculate the Euclidean distance between all the detected boxes and filter out or flag the people that are closest to each other indicating that they are at risk. So Would you like to learn how to make your own Social Distancing Monitoring App? Well, you are in luck cos' I have just uploaded a tutorial on how YOLOv4 can be used to monitor social distancing.  Check out the link: CLICK HERE : If you are interested in Enrolling in my upcoming course on YOLOv4 then sign up over here when it gets released - Click Here YOLOV4 Course - Coming Soon! Road Map Okay great! So now that we have YOLOv4 working, lets take a look out road map going forth: Tut

Darknet and YOLOV4 Installation Documentation Hey guys and welcome back, so in the last lecture, we spent some time setting up the prerequisites for YOLOv4, like Visual Studio, Python, CUDA, CuDnn and OpenCV. If you have not completed the previous tutorial, then I highly suggest that you do because this lecture builds upon the steps we took in the previous tutorial . So if you have completed that tutorial , then this lecture we are going to be installing Darknet Framework and thus YOLOv4. By the end of this tutorial you will be able to implement YOLOv4 on an Image and on Video. I’m sure you must be excited, Okay so let’s get into the tutorial. Watch the Full Video Tutorial Here Step 1 Cloned repository from official Github of AlexyAB [link] Step 2 Copy OpenCV_ffmpeg and _world dll’s for 4.1.0 version(can be used for OpenCV video processing) near to darknet.exe Step 3 Copied cuDNN.dll(for accelerating the neural network processes) near to darknet.exe Step 4 Change the CUDA version if yo

Tutorial on YouTube Introduction Hey guys and welcome back, so in the last lecture, I spoke about how YOLOv4 works and why its so awesome! Today I’m going to show you how to install the main dependencies in 10 Steps. If you follow these steps with me you should be able to get YOLOv4 working on images, videos and webcams in the upcoming tutorials. Let’s go through the 10 steps that we need to for YOLOv4 . Install Python Git Installation CMake Installation Visual Studio Installation Updating GPU Driver CUDA installation CuDNN Installation OpenCV Installation CMake OpenCV Configuration, and Building OpenCV in Visual Studio It may seem like a lot of steps but, it is more reliable that using Anaconda to install everything. Well at least from my experience. Some Prerequisites that you will need for this tutorial: Are a mid to high range PC/Laptop Windows 10, we will be launching an Ubuntu version of this YOLOv4 soon., and A CUDA supported NVIDIA GPU, Just note that this will NOT work on