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Table of contents
1.
Introduction
2.
Computer vision
3.
About OpenCV
4.
Setting up OpenCV
5.
Some important OpenCV functions
6.
Applications of OpenCV
7.
Frequently Asked Questions
8.
Conclusion
Last Updated: Mar 27, 2024
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Introduction to OpenCV

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Introduction

Computer vision is one of the most trending fields of computer science that allows computers or machines to perceive and understand the world through images. Computer vision has made previously thought technologies like driverless cars a reality. OpenCV is an open-source library used for computer vision and image processing. OpenCV is available for different programming languages such as C++ and python. Let us learn more about OpenCV.

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Computer vision

Computer vision (abbreviated as CV) focuses on making computers see and understand images. It uses various algorithms to learn from the training data, usually including thousands or even millions of images. Computer vision is used in many industries.

Computer vision is a reliable technology, and we use it almost everywhere. We unknowingly use computer vision every day when we unlock our phones using face detection or search for something on the internet using images.

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About OpenCV

OpenCV is an open-source computer vision library that can work with Windows, Linux, Mac OS, ios, and android. It has interfaces with multiple programming languages such as C++, Python, and Java. It is a BSD-licensed product and is free for commercial and academic use. OpenCV has more than 2500 algorithms that can perform various image processing tasks. OpenCV is written natively in C++ and works seamlessly with STL containers.

Setting up OpenCV

Let us now learn how to install OpenCV for python on windows. To install OpenCV for python, we must have python and pip installed on our system. To verify that you have python installed on your system or not, open the command prompt and execute this command 

python –version

 

If python is available, it will show a message like this below.

If python is not installed, you can download and install it using this link

  1. To install pip, follow this link. Once the pip installation is complete, verify the installation by using pip –version command.


     
  2. After getting python and pip on your system, use the pip install opencv-python to install OpenCV.opencv-py


     
  3. To check if OpenCV is installed correctly, run the following command:


    Also see, How to Check Python Version in CMD

Some important OpenCV functions

Some of the most common OpenCV functions are:

  • cv2.imread()
    This function is used to read the image from the specified path.
     
  • cv2.imread_grayscale()
    The image is generally changed to grayscale before processing. We can change the image into grayscale by using this method.
     
  • cv2.imshow()
    It is used to display an image in a window.
     
  • cv2.resize()
    Used to resize an image
     
  • cv2.flip()
    It is used to flip an image. We can choose the axis around which we want to flip the image.
     
  • cv2.Canny()
    It is used for edge detection. 

Applications of OpenCV

Some of the common applications of OpenCV are:

  • Facial recognition.
  • Object detection
  • Image processing
  • Medical image analysis
  • Driverless cars navigation
  • Robotic vision
    Also read, Sampling and Quantization

Frequently Asked Questions

  1. Which language is best suitable for OpenCV?
    C++ is considered best for OpenCV as it is natively written in it.
     
  2. Where OpenCV libraries are installed?
    The OpenCV libraries are installed in the lib folder in your OpenCV directory on Windows.
     
  3. How is a digital image formed?
    A digital image is formed by the arrangement of pixels in an array.

Conclusion

In this blog, we talked about OpenCV. We learned how it can be used for different computer vision tasks. We also learned to set up OpenCV on our computer. Do check out the official documentation of OpenCV for more. To understand more about computer vision applications, check out this blog.

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