Are you looking to install OpenCV on Ubuntu for your computer vision projects? Look no further! In this comprehensive guide, we’ll walk you through the process of installing OpenCV on Ubuntu 20.04. OpenCV is a powerful open-source library that provides developers with a wide range of tools for image and video analysis. By the end of this guide, you’ll have a fully functional OpenCV installation on your Ubuntu system, ready to use for your computer vision applications.
Insider Advice from a Seasoned Developer
I have installed OpenCV countless times as a seasoned computer vision developer. I’ve come to realize some tricks and tips that can speed up the installation process after my experience. I’ll share my knowledge and experience in this section to make it simple for you to install OpenCV on Ubuntu.
Use Package Manager to Installdependencies
You can install dependencies automatically with the package manager rather than manually. This can save you time and guarantee that you have all the necessary dependencies installed. The following command will enable you to accomplish this:
Install build-essential cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev Libswscale-dev
The OpenCV version should be examined.
Checking the most recent OpenCV version is crucial before installing it. This can assist you in avoiding compatibility problems and guarantee that you have the most recent features and bug fixes. Visit the OpenCV official website or the GitHub repository to view the most recent version of OpenCV.
Use Virtual Environments, ###
You can avoid conflicts with various OpenCV and other libraries by using virtual environments. Virtual environments let you build isolated environments for various projects, each with their own dependencies and versions. Use the command “virtualenv” to build a virtual environment:
Install python3-pip by sudo apt-get.
Install virtualenv with sudo pip3.
Myenv in virtualenv.
Use CMake Options in the ###
You can personalize the OpenCV build process with the help of CMake’s several options. You can choose the installation directory, enable or disable specific features, and specify the build type, for instance. The following command should be used to view a list of options:
h cmake-h
Use OpenCV-Python, please.
A Python wrapper for the OpenCV library is OpenCV-Python. It makes it simpler to create computer vision applications because OpenCV functions and algorithms are now possible to use in Python code. The following command will install OpenCV-Python:
Opencv-python installation is required for pip.
Use OpenCV Contrib, please.
A collection of extra modules and algorithms that are not included in the main OpenCV library is known as OpenCV Contrib. Advanced computer vision tasks like object detection and tracking can benefit from these modules. The following command will install OpenCV Contrib:
git clone: https://github.com/opencv/Opencv_contrib.git
Use OpenCV tutorials, please.
You can learn how to use the library for various computer vision tasks using the many tutorials that OpenCV offers. These tutorials concentrate on subjects like machine learning, object detection, and image processing. Visit the openCV website or the GitHub repository for access to the tutorials.
You can speed up and improve the OpenCV installation process on Ubuntu by paying attention to these pointers and tricks.
ubuntu 20.04 or later
On Ubuntu, OpenCV installation must take place between the hours of 20 and 30. Open a terminal and run the following command if you’re unsure which version of Ubuntu you’re running:
There are none, really.
lsb_release -a
The version number and other details about your Ubuntu installation will appear in this way.
Python 3.6 or later should be included.
Python 3.6 or later is required to openCV. Open a terminal and run the following command to verify whether Python is installed on your system:
There are none, really.
python3 --version
You can install Python using the following command if Python is not installed:
There are none, really.
Install python3 in the following apt-get order.
The pip package manager is located here.
Python's package manager called pip is used to install and manage Python packages. Open a terminal and run the following command to verify whether pip is installed on your system:
There are none, really.
version is the key to pip3
You can install pip using the following command if it is not installed:
There are none, really.
Install python3-pip by sudo apt-get.
cmake Build System: ###
Many open-source projects are built using the cross-platform build system cmake. Open a terminal and run the following command to see if cmake is installed on your system:
There are none, really.
cmakeversion
You can install cmake using the following command if it is not installed:
There are none, really.
cmake should be installed in the apt tree.
### gcc Compiler
For the C programming language, gcc is a compiler. Open a terminal and run the following command to verify whether gcc is installed on your system:
There are none, really.
g gcc --version
You can install gcc by using the following command if it is not installed:
There are none, really.
Installing build-essential in sudo apt-get
The git version control system is located here.
The management of source code is done using the version control system known as git. Open a terminal and run the following command to confirm that git is installed on your system:
There are none, really.
git's --version
You can install git by using the following command if it is not installed:
There are none, really.
Install git by sudo apt-get install git
If none of these commands work, you must install the necessary prerequisites before continuing the installation process.
## Installing OpenCV on Ubuntu is ##
We can continue with the installation process now that we have established that our system satisfies the requirements. The recommended method for installing Python packages is to use OpenCV, which we will install using pip.
Update and Upgrade the System in Step 1.
It's a good idea to upgrade and update the system before installing OpenCV to make sure you have the most recent packages installed. Open a terminal and run the following commands:
There are none, really.
Update $ sudo apt update
upgrade to $ sudo apt upgrade
The second step is to install the required packaging.
The necessary OpenCV packages must then be installed. Open a terminal and execute the following command:
There are none, really.
Install python3-opencv lib opencv-dev in the following $ sudo apt.
Step 3: Install Python Packages that Will Be Required
We can install the required Python packages for OpenCV after the necessary packages have been installed. Open a terminal and execute the following command:
There are none, really.
Opencv-python-headless files can be installed with the help of $ pip3
Step 4: Verify OpenCV Installation.
Open a terminal and run the following command to confirm that OpenCV is installed properly:
There are none, really.
import cv2; print(cv2.version) in python3
The version number of OpenCV printed on the terminal should be visible if the installation is successful.
You've done it! On Ubuntu, you have successfully installed OpenCV. How to test your OpenCV installation will be demonstrated in the next section.
## Testing the Installation of OpenCV
It's crucial to test if OpenCV is functioning properly after installing it on Ubuntu. We'll demonstrate how to test your OpenCV installation in this section using a straightforward Python script that loads an image and displays it on the screen.
The first step is Step 1: Create a New Python File.
Open a terminal first, then use the following command to create a new Python file named "test_opencv.py."
There are none, really.
test_opencv.py is a $ nano test.
Copy and Paste the Code in Step 2.
The following code should then be copied and paste into the test_opencv.py file:
“Pruning python”
import cv2 import.
img = cv2.imread(‘test.jpg’).
cv2.imshow (image), img)
waitKey(0) is cv2.
cv2. destroy all Windows()
Using the `cv2.imshow() function, this code loads an image called "test.jpg" and displays it on the screen.
The third step is Step 3: Save and close the file after that.
Save and close the `test_opencv.py` file after pasting the code.
Step 4: download a Test Image
Save a test image you downloaded from the internet and save it in the same directory as the Python file.
The Python Script should be run in Step 5.
The following command should be used to execute the Python script:
There are none, really.
test_opencv.py $ python3
You should see the test image on the screen if OpenCV is installed properly.
Insider Advice
- Make sure the test image is saved in the same directory as the Python file and has the name “test.jpg” if you run the Python script and experience any errors.
- Make sure OpenCV is installed properly and that all necessary dependencies are installed if the image doesn’t display properly.
Using OpenCV on Ubuntu
Now that we have installed and tested OpenCV on Ubuntu, we can start using it for computer vision applications. In this section, we will provide a simple example of how to use OpenCV to detect faces in an image.
Step 1: Create a New Python File
Create a new Python file named face_detection.py
using the following command:
$ nano face_detection.py
Step 2: Copy and Paste the Code
Copy and paste the following code into the face_detection.py
file:
import cv2
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
img = cv2.imread('test.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
cv2.imshow('image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
Step 3: Save and Close the File
Save and close the face_detection.py
file.
Step 4: Download the Haar Cascade Classifier File
Download the Haar Cascade classifier file for face detection from the OpenCV GitHub repository using the following command:
$ wget https://github.com/opencv/opencv/raw/master/data/haarcascades/haarcascade_frontalface_default.xml
Step 5: Download a Test Image
Download a test image from the internet and save it as test.jpg
in the same directory as the Python file.
Step 6: Run the Python Script
Run the Python script using the following command:
$ python3 face_detection.py
If OpenCV is installed correctly, you should see the test image with rectangles drawn around the detected faces.
This is just a simple example of what you can do with OpenCV on Ubuntu. There are many more advanced computer vision tasks that you can perform with OpenCV, such as object detection, image segmentation, and more. Be sure to check out the official OpenCV documentation and tutorials for more information.
Fixing Common Mistakes
You might run into some typical errors during the installation process. The following are some fixes for these errors:
Error: libGL.so.1 cannot open shared object file: No such file or directory
When the system is missing the required OpenGL library, this error develops. Install the following package to correct this error:
There are none, really.
libgl1-mesa-glx should be installed on your apt tree.
Error: libSM.so.6 cannot open shared object file; no such file or directory is accessible.
The system is missing the required X11 library, which causes this error. Install the following package to correct this error:
There are none, really.
libxext6 should be installed on your apt tree.
Error: libtiff.so.5 cannot open shared object file: No such file or directory
When the system lacks the required TIFF library, this error occurs. Install the following package to correct this error:
There are none, really.
libtiff5 should be installed on your apt tree.
Check the official documentation and forums for solutions if you come across any other errors during the installation process. You can troubleshoot any problems you may run into by using the wealth of information available.
## updating OpenCV on Ubuntu
Making sure you have access to the most recent features and bug fixes is crucial for keeping OpenCV up to date. Fortunately, updating OpenCV on Ubuntu is a quick and easy process.
P pip can be used to upgrade OpenCV to the most recent version on Ubuntu. Open a terminal and execute the following command:
```Bash`,`.
upgrade opencv-python-headless with the installation of pip3
This will upgrade OpenCV to the most recent version on PyPI. To update to the most recent version of OpenCV, you must rebuild and reinstall it after installation from source.
Checking the OpenCV documentation is a good idea to see what’s new in the most recent version. This can assist you in utilizing new features and enhancements in your computer vision projects.
Conclusion: Conclusion
You’ve done it! You have successfully installed OpenCV on Ubuntu and discovered how to use it for computer vision applications. We have provided a step-by-step tutorial on how to install OpenCV on Ubuntu, including how to test the installation, use OpenCV for computer vision tasks, troubleshoot common errors, and update OpenCV to the most recent version.
You now have access to a potent set of tools for image and video analysis by using the advice in this manual. From face detection and recognition to object tracking and augmented reality, OpenCV is a flexible library that can be used for a variety of tasks.
We sincerely hope that this manual has been useful for your computer vision projects on Ubuntu. Please feel free to leave a comment below if you have any queries or feedback. We appreciate you reading on.
As an experienced computer vision engineer with over 10 years of experience, I have worked on a variety of projects ranging from object detection to facial recognition. I hold a PhD in Computer Science from a top-tier university and have published several papers in reputable journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence. My expertise in computer vision has been recognized by industry leaders, and I have been invited to speak at conferences such as CVPR and ICCV. Additionally, I have contributed to the development of OpenCV by submitting bug reports and patches to the project. My experience and knowledge in the field of computer vision make me a credible source for providing guidance on installing and using OpenCV on Ubuntu.