Ashok's Programming World

Qt is a cross-platform application framework. Using Qt, you can write applications once and deploy them across many desktop and embedded operating systems without rewriting the source code.

Qt's vision is to have Qt Everywhere and to enable you to create advanced applications with innovative user experiences while getting to market quickly. Qt allows you to code once and deploy across major device and desktop operating systems.

  wxWidgets is a programmer’s toolkit for writing desktop or mobile applications with graphical user interfaces(GUIs). It’s a framework, in the sense that it does a lot of the housekeeping work and provides default application behavior. The wxWidgets library contains a large number of classes and methods for the programmer to use and customize. Applications typically show windows containing standard controls, possibly drawing specialized images and graphics and responding to input from the mouse, keyboard, or other sources. They may also communicate with other processes or drive other programs. In other words, wxWidgets makes it relatively easy for the programmer to write an application that does all the usual things modern applications do. While wxWidgets is often labeled a GUI development toolkit, it is in fact much more than that and has features that are useful for many aspects of application development. This has to be the case because all of a wxWidgets application needs to be portable to different platforms, not just the GUI part, wxWidgets provides classes for files and streams, multiple threads, application settings, interprocess communication, online help, database access, and much more.

What Is OpenCV?

OpenCV [OpenCV] is an open source (see http://opensource.org) computer vision library available from http://SourceForge.net/projects/opencvlibrary. Th e library is written in C and C++ and runs under Linux, Windows and Mac OS X. Th ere is active development on interfaces for Python, Ruby, Matlab, and other languages.

One of OpenCV’s goals is to provide a simple-to-use computer vision infrastructure that helps people build fairly sophisticated vision applications quickly. Th e OpenCV library contains over 500 functions that span many areas in vision, including factory product inspection, medical imaging, security, user interface, camera calibration, stereo vision, and robotics. Because computer vision and machine learning oft en go hand-inhand, OpenCV also contains a full, general-purpose Machine Learning Library (MLL). Th is sublibrary is focused on statistical pattern recognition and clustering. Th e MLL is highly useful for the vision tasks that are at the core of OpenCV’s mission, but it is general enough to be used for any machine learning problem.