Smooth or blur, gaussian blur, and noise-canceling, This tutorial will learn OpenCV blur, GaussianBlur, median blur functions in C++. Additionally, the advanced technique for noise reduction  fastNlMeansDenoising family  will be introduced with a code example for each method.   You can use blurring of the image to hide identity or reduce the noise of the image.  Blur can be a very useful operation and it is a very common operation as well. For example, the anonymization of pedestrians, face or is one possible target for blue operation. The blur is the most common task to perform over the image to reduce noise. The noise reduction is more task for Gaussian blur than for simple blur operation. The various blur operations are very common for image processing on mobile devices.  The more important is the robustness issues of the data in pre-processing for machine learning. Sometimes, by blurring the images of the dataset can have a positive effect on the robustness of the achieved de

This tutorial will learn you how to use deep neural networks by Yolo Darknet to detect multiple classes of objects. The code is under 100 lines of simple code. The code is using yolov3-tiny.weights of neural network and appropriate configuration yolov3-tiny.cfg. The code is presented as simple as possible, without the staff nice to have,  but not necessary to understand the flow of the code.  Yolo darknet in opencv OpenCV 4.x requirements for DNN module running Yolo (yolov3-tiny) I am using OpenCV 4.2 compiled on windows machines with contribution modules. I do not compile OpenCV with any special backend, like Cuda and, etc. You can found the description of how to compile OpenCV by CMake for Visual Studio 2019 here  on my blog. Just exclude the GStreamer related specialties.  How to setup Opencv Visual Studio 2019 Project This is very common. No big deal here. In project properties for Release configuration and Platform for x64 the additional include directories point in