There are many ways in which you can install OpenCV on your computer. OpenCV-Python is a Python wrapper for the original OpenCV C++ implementation.
Doing this, the code is fast, as it is written in original C/C++ code (since it is the actual C++ code working in the background) and also, it is easier to code in Python than C/C++. Python is a user friendly language and easy to work with but this advantage comes with a cost of speed, as Python is slower to languages such as C or C++.So we extend Python with C/C++, which allows us to write computationally intensive code in C/C++ and create Python wrappers that can be used as Python modules. The library has more than 2500 optimised algorithms, including an extensive collection of computer vision and machine learning algorithms, both classic and state-of-the-art.Using OpenCV it becomes easy to do complex tasks such as identify and recognise faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D object models, generate 3D point clouds from stereo cameras, stitch images together to generate an entire scene with a high resolution image and many more. This library is based on optimised C / C++ and supports Java and Python along with C++ through an interface. Gary Bradsky invented OpenCV in 1999 and soon the first release came in 2000. There are some predefined packages and libraries that make our life simple and OpenCV is one of them.
OpenCV, as a BSD-licensed software, makes it simple for companies to use and change the code. OpenCV was created to provide a shared infrastructure for applications for computer vision and to speed up the use of machine perception in consumer products.
OpenCV ( Open Source Computer Vision Library) is an open source software library for computer vision and machine learning. In more simpler terms we can say that a digital image is actually formed by the combination of three basic colour channels Red, green, and blue whereas for a grayscale image we have only one channel whose values also vary from 0-255. All other colours are represented by the numbers between 0 and 1.īut usually, you will find that for any colour image, there are 3 primary channels – Red, green and blue and the value of each channel varies from 0-255. The darker pixels are represented by a number closer to the zero and lighter pixels are represented by numbers approaching one. Here is a hypothetical example of how pixels form an image. So the computer sees an image as numerical values of these pixels and in order to recognise a certain image, it has to recognise the patterns and regularities in this numerical data. But does a computer also see it in the same way? The answer is no.Ī digital image is an image composed of picture elements, also known as pixels, each with finite, discrete quantities of numeric representation for its intensity or grey level. You most probably look for different shapes and colours in the Image and that might help you decide that this is an image of a dog.