OpenCV (Open Source Computer Vision Library) is an open-source library of computer vision and machine learning algorithms. It is widely used in computer vision and image processing applications. In this article, we will discuss how to check the version of OpenCV installed on your system using the command line.
There are several ways to check the version of OpenCV installed on your system. One of the most common methods is to use the pkg-config command. The pkg-config command is a command-line tool that is used to retrieve information about installed libraries in a system. To check the version of OpenCV installed on your system using pkg-config, open the terminal and type the following command:
pkg-config --modversion opencv
This command will return the version of OpenCV installed on your system. For example, if the version of OpenCV installed on your system is 4.5.0, the command will return "4.5.0".
Another way to check the version of OpenCV installed on your system is to use the python interpreter. OpenCV can be imported into python and version can be checked from the module. To check the version of OpenCV installed on your system using Python, open the terminal and type the following command:
python
import cv2
print(cv2.__version__)
This will also return the version of OpenCV installed on your system. For example, if the version of OpenCV installed on your system is 4.5.0, the command will return "4.5.0".
Lastly, you can also check the version of OpenCV installed on your system by using the OpenCV's function getVersionInfo.
import cv2
print(cv2.getVersionInfo())
This function will return the version of opencv, version of opencv_contrib, and the version of the build.
In conclusion, checking the version of OpenCV installed on your system is a simple task that can be accomplished using the command line or python interpreter. The pkg-config command, python imports and OpenCV's own function are some of the ways to check the version of OpenCV installed on your system. It is important to know the version of OpenCV installed on your system as it can help you determine if you have the correct version for a specific application or if you need to upgrade to a newer version.
Another important aspect of working with OpenCV is understanding how to install it on your system. OpenCV can be installed on various operating systems including Windows, MacOS, and Linux. The installation process for each operating system is slightly different.
For Windows, the easiest way to install OpenCV is by using the pre-built binary distributions that are available on the OpenCV website. You can download the appropriate binary distribution for your system (32-bit or 64-bit) and install it by following the instructions provided.
For MacOS, you can install OpenCV using the package manager Homebrew. The following command installs OpenCV on MacOS:
brew install opencv
For Linux, you can install OpenCV by building it from the source. This involves downloading the source code, configuring the build, and compiling it. You can also install OpenCV using package manager of your distro.
sudo apt-get install libopencv-dev
Once OpenCV is installed on your system, you can start using it in your projects. OpenCV provides a wide range of functionality, including image processing, object detection, and machine learning. You can use OpenCV to develop various applications such as facial recognition, object tracking, and image stitching.
To start using OpenCV in your projects, you need to import the library in your code. In Python, you can import OpenCV using the following command:
import cv2
In C++, you can import OpenCV using the following command:
#include <opencv2/opencv.hpp>
Additionally, OpenCV has a large community of developers who have created many useful resources such as tutorials, sample code, and pre-trained models. This can be very helpful when you are learning to use OpenCV or when you are developing a new project. The OpenCV website also provides detailed documentation for all of its functions and modules, which can be very helpful when you are trying to understand how a specific function works.
In summary, OpenCV is a powerful open-source library of computer vision and machine learning algorithms that can be used for a wide range of applications. It is important to understand how to install OpenCV on your system and how to import the library into your projects. With the help of the large community of developers, learning OpenCV and developing projects with it can be a smooth process.
Popular questions
- How can I check the version of OpenCV installed on my system using the command line?
- You can check the version of OpenCV installed on your system using the pkg-config command by typing
pkg-config --modversion opencvin the terminal.
- Can I check the version of OpenCV installed on my system using Python?
- Yes, you can check the version of OpenCV installed on your system using Python by importing the library and using the command
print(cv2.__version__)
- Is there a built-in function in OpenCV to check the version?
- Yes, OpenCV has its own function
cv2.getVersionInfo()which will return the version of opencv, version of opencv_contrib, and the version of the build.
- How can I install OpenCV on my Windows system?
- The easiest way to install OpenCV on Windows is by using the pre-built binary distributions that are available on the OpenCV website. You can download the appropriate binary distribution for your system (32-bit or 64-bit) and install it by following the instructions provided.
- Is there a community of developers that can help me learn and use OpenCV?
- Yes, OpenCV has a large community of developers who have created many useful resources such as tutorials, sample code, and pre-trained models. The OpenCV website also provides detailed documentation for all of its functions and modules, which can be very helpful when you are trying to understand how a specific function works.
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