Skip to content
- Tutorials
- Python Tutorial
- Taking Input in Python
- Python Operators
- Python Data Types
- Python Loops and Control Flow
- Python Functions
- Python OOPS Concept
- Python Data Structures
- Python Exception Handling
- Python File Handling
- Python Exercises
- Java
- Java Programming Language
- Java Collections
- Java 8 Tutorial
- Java Programs
- Java Interview Questions
- Java Exercises
- Java Quiz
- Java Projects
- Advance Java
- Programming Languages
- System Design
- Interview Corner
- Computer Science Subjects
- DevOps
- Linux
- Software Testing
- Databases
- Android
- Excel
- Mathematics
- Commerce
- Aptitude
- Python Tutorial
- DSA
- Data Structures
- Algorithms
- Analysis of Algorithms
- Searching Algorithms
- Sorting Algorithms
- Greedy Algorithms
- Dynamic Programming
- Graph Algorithms
- Pattern Searching
- Recursion
- Backtracking
- Divide and Conquer
- Mathematical Algorithms
- Geometric Algorithms
- Bitwise Algorithms
- Randomized Algorithms
- Branch and Bound
- Algorithms Tutorial
- DSA Tutorial
- Practice
- All DSA Problems
- Problem of the Day
- Company Wise Coding Practice
- GfG SDE Sheet
- Practice Problems Difficulty Wise
- Language Wise Coding Practice
- Curated DSA Lists
- Competitive Programming
- Company Wise SDE Sheets
- DSA Cheat Sheets
- Top Interview Questions
- Puzzles
- Data Science
- Web Tech
- Courses
-
- OpenCV Tutorial in Python
- Essential OpenCV Functions to Get Started into Computer Vision
Getting Started
Working with Images - Getting Started
Working with Images - Image Processing
Working with Images - Feature Detection and Description
Working with Images - Drawing Functions
Working with Videos
Applications and Projects
OpenCV Projects
Last Updated : 18 Jan, 2023
Improve
Like Article
Like
Save
Report
Prerequisite: Python Language Introduction OpenCV is the huge open-source library for computer vision, machine learning, and image processing and now it plays a major role in real-time operation which is very important in today’s systems. By using it, one can process images and videos to identify objects, faces, or even the handwriting of a human. When it integrated with various libraries, such as Numpy, python is capable of processing the OpenCV array structure for analysis. To Identify image patterns and its various features we use vector space and perform mathematical operations on these features. To install OpenCV, one must have Python and PIP, preinstalled on their system. To check if your system already contains Python, go through the following instructions: Open the Command line(search for cmd in the Run dialog( + R). Now run the following command:
python --version
If Python is already installed, it will generate a message with the Python version available.
If Python is not present, go through How to install Python on Windows? and follow the instructions provided. PIP is a package management system used to install and manage software packages/libraries written in Python. These files are stored in a large “on-line repository” termed as Python Package Index (PyPI). To check if PIP is already installed on your system, just go to the command line and execute the following command:pip -V
If PIP is not present, go through How to install PIP on Windows? and follow the instructions provided.Downloading and Installing OpenCV:
OpenCV can be directly downloaded and installed with the use of pip (package manager). To install OpenCV, just go to the command-line and type the following command:
pip install opencv-python
Beginning with the installation:
- Type the command in the Terminal and proceed:
- Collecting Information and downloading data:
- Installing Packages:
- Finished Installation:
To check if OpenCV is correctly installed, just run the following commands to perform a version check:
python>>>import cv2>>>print(cv2.__version__)
Please Login to comment...
Similar Reads
OpenCV - Facial Landmarks and Face Detection using dlib and OpenCV
Content has been removed on Author's request.
1 min read
Transition from OpenCV 2 to OpenCV 3.x
OpenCV is one of the most popular and most used Computer vision libraries. It contains tools to carry out image and video processing. When OpenCV 3..4.1 is an improved version of OpenCV 2.4 as it introduced new algorithms and features. Although some of the existing modules were rewritten and moved to sub-modules. In this articles, I will focus on t
2 min read
Top Books for Learning OpenCV: Computer Vision with OpenCV Library
OpenCV or Open Source Computer Vision Library, is an open-source computer vision and machine learning software library. It's extensively used for real-time computer vision tasks such as object detection, face recognition, image processing, etc. Whether you're a beginner or an experienced developer looking to deepen your understanding of OpenCV, her
5 min read
Automatic Document Scanner using OpenCV (OpenCV Document Scanner)
An automatic document scanner using OpenCV is a computer vision application that automatically detects and extracts documents from images. This type of scanner can be useful in various scenarios, such as digitizing paper documents, processing scanned documents, or automating document recognition tasks. In this article, we will see how we can build
6 min read
How to Install the Windows Subsystem for Linux on Windows 11?
As a programmer, it is very important to test software on multiple platforms. However, it can be very tedious and inefficient to use multiple virtual machines to achieve the same. Thankfully, this process can be simplified if you are using Windows and wish to run a Linux distribution - with WSL. WSL, or Windows Subsystem for Linux, lets developers
2 min read
How to Download and Install Windows Movie Maker on Windows 10?
Movie Maker video is one of the best video editors available on the Microsoft store itself and is absolutely free. Movie maker video editor is a single-OS software, i.e. it works only in windows, and not on macOS, and Linux. Movie maker has more than 10 million users worldwide. Some of the very cool features of movie maker video editors are that th
2 min read
Opening multiple color windows to capture using OpenCV in Python
OpenCV is an open source computer vision library that works with many programming languages and provides a vast scope to understand the subject of computer vision.In this example we will use OpenCV to open the camera of the system and capture the video in two different colors. Approach: With the libraries available in OpenCV-Python below we will op
2 min read
How to Install OpenCV for Python in Linux?
Prerequisite: Python Language Introduction OpenCV is the huge open-source library for computer vision, machine learning, and image processing and now it plays a major role in real-time operation which is very important in today’s systems. By using it, one can process images and videos to identify objects, faces, or even the handwriting of a human.
2 min read
How to install OpenCV Contrib Python
OpenCV (Open Source Computer Vision Library) is a powerful open-source computer vision and machine learning software library. It provides various tools and algorithms for image and video processing, object detection, feature extraction, and more. OpenCV Contrib is an extension module that includes additional functionalities and algorithms contribut
2 min read
How to Install OpenCV Python Headless?
OpenCV (Open Source Computer Vision Library) is a powerful open-source computer vision and machine learning software library. It enables developers to access a wide range of algorithms for various computer vision tasks. In this article, we will see how to install OpenCV Python Headless. What is OpenCV Python Headless?Installing OpenCV in Python hea
2 min read
Article Tags :
Practice Tags :
We use cookies to ensure you have the best browsing experience on our website. By using our site, you acknowledge that you have read and understood our Cookie Policy & Privacy Policy
If Python is not present, go through 
If PIP is not present, go through 
'); $('.spinner-loading-overlay').show(); jQuery.ajax({ url: writeApiUrl + 'create-improvement-post/?v=1', type: "POST", contentType: 'application/json; charset=utf-8', dataType: 'json', xhrFields: { withCredentials: true }, data: JSON.stringify({ gfg_id: post_id, check: true }), success:function(result) { jQuery.ajax({ url: writeApiUrl + 'suggestions/auth/' + `${post_id}/`, type: "GET", dataType: 'json', xhrFields: { withCredentials: true }, success: function (result) { $('.spinner-loading-overlay:eq(0)').remove(); var commentArray = result; if(commentArray === null || commentArray.length === 0) { // when no reason is availaible then user will redirected directly make the improvment. // call to api create-improvement-post $('body').append('
'); $('.spinner-loading-overlay').show(); jQuery.ajax({ url: writeApiUrl + 'create-improvement-post/?v=1', type: "POST", contentType: 'application/json; charset=utf-8', dataType: 'json', xhrFields: { withCredentials: true }, data: JSON.stringify({ gfg_id: post_id, }), success:function(result) { $('.spinner-loading-overlay:eq(0)').remove(); $('.improve-modal--overlay').hide(); $('.unlocked-status--improve-modal-content').css("display","none"); $('.create-improvement-redirection-to-write').attr('href',writeUrl + 'improve-post/' + `${result.id}` + '/', '_blank'); $('.create-improvement-redirection-to-write')[0].click(); }, error:function(e) { $('.spinner-loading-overlay:eq(0)').remove(); var result = e.responseJSON; if(result.detail.non_field_errors.length){ $('.improve-modal--improve-content .improve-modal--improve-content-modified').text(`${result.detail.non_field_errors}.`); jQuery('.improve-modal--overlay').show(); jQuery('.improve-modal--improvement').show(); $('.locked-status--impove-modal').css("display","block"); $('.unlocked-status--improve-modal-content').css("display","none"); $('.improve-modal--improvement').attr("status","locked"); $('.improvement-reason-modal').hide(); } }, }); return; } var improvement_reason_html = ""; for(var comment of commentArray) { // loop creating improvement reason list markup var comment_id = comment['id']; var comment_text = comment['suggestion']; improvement_reason_html += `
${comment_text}
`; } $('.improvement-reasons_wrapper').html(improvement_reason_html); $('.improvement-bottom-btn').html("Create Improvement"); $('.improve-modal--improvement').hide(); $('.improvement-reason-modal').show(); }, error: function(e){ $('.spinner-loading-overlay:eq(0)').remove(); // stop loader when ajax failed; }, }); }, error:function(e) { $('.spinner-loading-overlay:eq(0)').remove(); var result = e.responseJSON; if(result.detail.non_field_errors.length){ $('.improve-modal--improve-content .improve-modal--improve-content-modified').text(`${result.detail.non_field_errors}.`); jQuery('.improve-modal--overlay').show(); jQuery('.improve-modal--improvement').show(); $('.locked-status--impove-modal').css("display","block"); $('.unlocked-status--improve-modal-content').css("display","none"); $('.improve-modal--improvement').attr("status","locked"); $('.improvement-reason-modal').hide(); } }, }); }); $('.left-arrow-icon_wrapper').on('click',function(){ if($('.improve-modal--suggestion').is(":visible")) $('.improve-modal--suggestion').hide(); else{ $('.improvement-reason-modal').hide(); } $('.improve-modal--improvement').show(); }); jQuery('.suggest-bottom-btn').on('click', function(){ var suggest_val = $.trim($("#suggestion-section-textarea").val()); var error_msg = false; if(suggest_val != ""){ if(suggest_val.length <= 2000){ jQuery('body').append('
'); jQuery('.spinner-loading-overlay').show(); jQuery.ajax({ type:'post', url: "https://apiwrite.geeksforgeeks.org/suggestions/auth/create/", xhrFields: { withCredentials: true }, crossDomain: true, contentType:'application/json', data: JSON.stringify({ "gfg_post_id" : `${post_id}`, "suggestion" : `
${suggest_val}
` }), success:function(data) { jQuery('.spinner-loading-overlay:eq(0)').remove(); jQuery('#suggestion-section-textarea').val(""); jQuery('.suggest-bottom-btn').html("Sent "); setTimeout(() => { jQuery('.improve-modal--overlay').hide(); $('.improve-modal--suggestion').hide(); }, 1000); }, error:function(data) { jQuery('.spinner-loading-overlay:eq(0)').remove(); jQuery('#suggestion-modal-alert').html("Something went wrong."); jQuery('#suggestion-modal-alert').show(); error_msg = true; } }); } else{ jQuery('#suggestion-modal-alert').html("Character limit exceeded."); jQuery('#suggestion-modal-alert').show(); jQuery('#suggestion-section-textarea').focus(); error_msg = true; } } else{ jQuery('#suggestion-modal-alert').html("Enter valid input."); jQuery('#suggestion-modal-alert').show(); jQuery('#suggestion-section-textarea').focus(); error_msg = true; } if(error_msg){ setTimeout(() => { jQuery('#suggestion-section-textarea').focus(); jQuery('#suggestion-modal-alert').hide(); }, 3000); } }) $('.improvement-bottom-btn.create-improvement-btn').click(function() { //create improvement button is clicked $('body').append('
'); $('.spinner-loading-overlay').show(); // send this option via create-improvement-post api jQuery.ajax({ url: writeApiUrl + 'create-improvement-post/?v=1', type: "POST", contentType: 'application/json; charset=utf-8', dataType: 'json', xhrFields: { withCredentials: true }, data: JSON.stringify({ gfg_id: post_id }), success:function(result) { $('.spinner-loading-overlay:eq(0)').remove(); $('.improve-modal--overlay').hide(); $('.improvement-reason-modal').hide(); $('.create-improvement-redirection-to-write').attr('href',writeUrl + 'improve-post/' + `${result.id}` + '/', '_blank'); $('.create-improvement-redirection-to-write')[0].click(); }, error:function(e) { $('.spinner-loading-overlay:eq(0)').remove(); var result = e.responseJSON; if(result.detail.non_field_errors.length){ $('.improve-modal--improve-content .improve-modal--improve-content-modified').text(`${result.detail.non_field_errors}.`); jQuery('.improve-modal--overlay').show(); jQuery('.improve-modal--improvement').show(); $('.locked-status--impove-modal').css("display","block"); $('.unlocked-status--improve-modal-content').css("display","none"); $('.improve-modal--improvement').attr("status","locked"); $('.improvement-reason-modal').hide(); } }, }); });
