01. November 2015       OpenCV, Tutorials

Lightning fast, beginner / intermediate level tutorials of real-world application of OpenCV library. This week covering image mosaicking.

 10. October 2015       Node.js, C++, Cloudcv

One of the problems I had to solve while working on CloudCV is a data marshalling from V8 engine to plain C++ objects and vice versa. In C++ add-on for Nodejs you need to parse and convert input arguments, which can be scalar types, collections and user-defined structures. Proposed library solves this task with least possible amount of headache.

 09. September 2015       News, Computer Vision Digest, C++

This article is a quintessence of my all experience I’ve got for last years working as a computer vision consultant. I hope you will find this interesting and useful. My goal was to create set of rules I follow personally on daily basis.

 14. April 2015       Tutorials, Node.js, Cloudcv, OpenCV

Here’s an open-source ready to use bootstrap project written in Node.js that lets you to quickly build a REST service to host your image processing and computer vision code in a cloud environment. Please welcome: cloudcv-bootstrap.

 17. March 2015       Tutorials, Node.js, Visual Studio

While working on CloudCV I encountered problems in node.js addon written in native code. For CloudCV I use node.js with C++ Addon to separate high-performance algorithms (C++) from high-level networking API which node provides.

In this tutorial I’m going to reveal best practices on debugging C++ Addons for Node.js (0.12) using Visual Studio 2013.

Continue reading if you want to read in details why this works.

 25. December 2014       OpenCV

This post convers very specific but important topic about writing memory-efficient code. I will show you how to collect and analyze memory allocations that happens in OpenCV.

When it comes to writing efficient code we usually care about CPU-efficiency. However there are many times, when memory-efficiency is more important. A limited amount of RAM is not so rare as one can think. On iOS and Android there are a strict memory usage restrictions, and of your app uses more memory than allowed your app can get killed by the system. Embedded hardware systems used in IoT, Raspberri Pi and others also have very limited amount of RAM. So you should be very careful when porting code from desktop with gigabytes of memory to mobile platform.

 04. December 2014       OpenCV, Tutorials, Algorithms

How would you design an algorithm to process 40Mpx image? 100Mpx? What about gigapixel-sized panorams? Obviously, it should differs from those that are intended for 640x480 images. Here I want to present you implementation of the very simple but powerful approach called “Tile-based image processing”. I will show you how to make this using OpenCV.

Tile based image processing