OpenCV: A library for image processing in Python

In this article, you will learn about the function library ‘OpenCV’ in a general way, along with a slight inclination to the programming language Python.

OpenCV (Open Source Computer Vision) is a programming library of multiple functions designed to undertake tasks of image processing or tasks related to that. In layman’s terms, it is to make the machine understand and process various types of images, making the user able to use it in multiple practical situations. It’s most common uses include detection of faces and facial features, text interpretation, shape detection, and much more.

OpenCV and its Functionality

OpenCV is a mighty library and is being incorporated by users in many real-world projects. For example, street view, 3D imaging, and augmented reality are some of the most common uses of this library.

In general, the many functionalities of OpenCV have been listed by me below:

• Image and video, Input/Output, processing, display.
• Object/feature detection.
• Geometry-based monocular or stereo computer vision.
• Computational photography.
• Machine learning & clustering.
• CUDA(Compute Unified Device Architecture)  acceleration.

Here are some tutorials of OpenCV that might help you:

• Detect number of faces from an image in Python using OpenCV
• Capture and save webcam video in Python using OpenCV
• Color filtering with OpenCV in python

Through these functionalities, there have been many code models to serve a specific purpose. Some of them are facial recognition, curved lane detection for roads, pothole detection, blood sample processing, motion detection, etc. and this is just the start.

By combining this library with a variety of other hardware, software, and other libraries, we can expand the range of tasks our program can perform. As a result, we can expand our skill-set and project range. For instance, we can combine our project with RaspberriyPi to create a voice-controlled bot,

 

To import openCV onto your computer, we have two methods: direct download from pypi.org and looking for the library ‘cv2’. The alternative (and a relatively shorter process) is to open the terminal/command prompt and type:

Microsoft Windows [Version 10.0.17763.805]
(c) 2018 Microsoft Corporation. All rights reserved.

C:\Users\HP>pip install cv2

To incorporate it into your python program, write

import cv2

at the start of your application. As a result, you will now be able to use this fantastic and powerful library in your projects.

We want you to generate your own OpenCV projects and hope you like this tutorial. If you have any doubts, feel free to comment below this article.

 

You may also like to read:

Creating a Slow-motion Video Using OpenCV in Python