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The name of the virtual environment. To exit the virtual environment, use the deactivate command.Once inside the virtual environment, you can now install OpenCV. Execute the command below.pip3 install opencv-pythonInstall OpenCV with pipFrom the image above, you can see we have successfully installed OpenCV version 4.5.1.48. That’s it! You are done with OpenCV installation. To test OpenCV in your project, skip to the Test section at the bottom of the article.Method 2: Install OpenCV from the sourceIf you need a full installation of OpenCV, which includes patented algorithms, then you should use this method. Unlike the pip install method, which only takes a couple of minutes, compiling OpenCV from the source can take around two (2) hours. Follow the steps below:Step 1. Activate your virtual environment with the workon command below.workon sbb_cvStep 2. Download the source code for both OpenCV and Opencv_contrib from Github. Use the wget commands below.wget -O opencv_contrib.zip -O opencv.zip you get an error like ‘wget command not found,’ then you will need to install it with the command – sudo apt install wgetStep 3. We need to unzip the contents of the two files we downloaded. Use the unzip command as shown below:unzip opencv.zipunzip opencv_contrib.zipStep 4. After extracting the zip files, we will have two folders – opencv-4.5.2 and opencv_contrib-4.5.1. Let’s rename these two to something memorable like opencv and opencv_contrib.mv opencv-4.5.2 opencvmv opencv_contrib-4.5.1 opencv_contribRename foldersStep 5. Compiling OpenCV can be quite heavy on the Raspberry Pi memory. To avoid freezing or hanging, we can increase the SWAP space and utilize all four cores of the Pi in the compiling process. To do so, we will edit the dphys-swapfile present in the /etc. directory. Execute the command below to open dphys-swapfile with the nano editor.sudo nano /etc/dphys-swapfileFind the line – CONF_SWAPSIZE and set its value to

Sure you are in the cv virtual environment:$ workon cvFollowed by setting up the build:$ cd ~/opencv-3.0.0/$ mkdir build$ cd build$ cmake -D CMAKE_BUILD_TYPE=RELEASE \ -D CMAKE_INSTALL_PREFIX=/usr/local \ -D INSTALL_C_EXAMPLES=ON \ -D INSTALL_PYTHON_EXAMPLES=ON \ -D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib-3.0.0/modules \ -D BUILD_EXAMPLES=ON ..Update (3 January 2016): In order to build OpenCV 3.1.0 , you need to set -D INSTALL_C_EXAMPLES=OFF (rather than ON ) in the cmake command. There is a bug in the OpenCV v3.1.0 CMake build script that can cause errors if you leave this switch on. Once you set this switch to off, CMake should run without a problem.Before you move on to the compilation step, make sure you examine the output of CMake!Scroll down the section titled Python 2 and Python 3 .If you’re compiling OpenCV 3 for Python 2.7, then you’ll want to make sure the Python 2 section looks like this (highlighted) in red:Figure 3: Ensuring that Python 2.7 will be used for the compile.Notice how both the Interpreter and numpy variables point to the cv virtual environment.Similarly, if you’re compiling OpenCV for Python 3, then make sure the Python 3 section looks like this:Figure 4: Ensuring that Python 3 will be used for the compile.Again, both the Interpreter and numpy variables are pointing to our cv virtual environment.In either case, if you do not see the cv virtual environment for these variables MAKE SURE YOU ARE IN THE cv VIRTUAL ENVIRONMENT PRIOR TO RUNNING CMAKE!Now that our build is all setup, we can compile OpenCV:$ make -j4Timing: 1h 35mThe -j4 switch stands for the number of cores to use when compiling OpenCV. Since we are using a Raspberry Pi 2, we’ll leverage all four cores of the processor for a faster compilation.However, if your make command errors out, I would suggest starting the compilation over again and only using one core:$ make clean$ makeUsing only one core will take much longer to compile, but can help reduce any type of strange race dependency condition errors when compiling.Assuming OpenCV compiled without error, all we need to do is install it on our system:$ sudo make install$ sudo ldconfigStep

#5: Finishing the installWe’re almost there! Just a few more things and we’ll be 100% done.For Python 2.7:Provided you finished Step #4 without error, OpenCV should now be installed in /usr/local/lib/python2.7/site-packages :$ ls -l /usr/local/lib/python2.7/site-packages/total 1636-rw-r--r-- 1 root staff 1675144 Oct 17 15:25 cv2.soNote: In some instances OpenCV can be installed in /usr/local/lib/python2.7/dist-packages (note the dist-packages rather than site-packages ). If you do not find the cv2.so bindings in site-packages , be sure to check dist-packages as well.The last step here is to sym-link the OpenCV bindings into the cv virtual environment:$ cd ~/.virtualenvs/cv/lib/python2.7/site-packages/$ ln -s /usr/local/lib/python2.7/site-packages/cv2.so cv2.soFor Python 3:OpenCV should now be installed in /usr/local/lib/python3.4/site-packages :$ ls /usr/local/lib/python3.4/site-packages/cv2.cpython-34m.soFor some reason, unbeknownst to me, when compiling the Python 3 bindings the output .so file is named cv2.cpython-34m.so rather than cv2.so .Luckily, this is an easy fix. All we need to do is rename the file:$ cd /usr/local/lib/python3.4/site-packages/$ sudo mv cv2.cpython-34m.so cv2.soFollowed by sym-linking OpenCV into our cv virtual environment:$ cd ~/.virtualenvs/cv/lib/python3.4/site-packages/$ ln -s /usr/local/lib/python3.4/site-packages/cv2.so cv2.soStep #6: Verifying your OpenCV 3 installAt this point, OpenCV 3 should be installed on your Raspberry Pi running Raspbian Jessie!But before we wrap this tutorial up, let’s verify that your OpenCV installation is working by accessing the cv virtual environment and importing cv2 , the OpenCV + Python bindings:$ workon cv$ python>>> import cv2>>> cv2.__version__'3.0.0'You can see a screenshot of my terminal below, indicating that OpenCV 3 has been successfully installed:Figure 5: OpenCV 3 + Python 3 bindings have been successfully installed on my Raspberry Pi 2 running Rasbian Jessie.TroubleshootingQ. When I try to use the mkvirtualenv or workon commands, I get an error saying “command not found”.A. Go back to Step #3 and ensure your ~/.profile file has been updated properly. Once you have updated it, be sure to run source ~/.profile to reload it.Q. After I reboot/logout/open up a new terminal, I cannot run the mkvirtualenv or workon commands.A. Anytime you reboot your system, logout and log back in, or open up a new terminal, you should run source ~/.profile to make sure you have access to your Python virtual environments.Q. When I

A few weeks ago Raspbian Jessie was released, bringing in a ton of new, great features.However, the update to Jessie also broke the previous OpenCV + Python install instructions for Raspbian Wheezy:Install OpenCV 2.4 with Python 2.7 bindings on Raspbian Wheezy.Install OpenCV 3.0 with Python 2.7/Python 3+ bindings on Raspbian Wheezy.Since PyImageSearch has become the online destination for learning computer vision + OpenCV on the Raspberry Pi, I decided to write a new tutorial on installing OpenCV 3 with Python bindings on Raspbian Jessie.As an additional bonus, I’ve also included a video tutorial that you can use to follow along with me as I install OpenCV 3 on my own Raspberry Pi 2 running Raspbian Jessie.This video tutorial should help address the most common questions, doubts, and pitfalls that arise when installing OpenCV + Python bindings on the Raspberry Pi for the first time.AssumptionsFor this tutorial I am going to assume that you already own a Raspberry Pi 2 with Raspbian Jessie installed. Other than that, you should either have (1) physical access to your Pi 2 and can open up a terminal or (2) remote access where you can SSH in. I’ll be doing this tutorial via SSH, but as long as you have access to a terminal, it really doesn’t matter.The quick start video tutorialBefore we get this tutorial underway, let me ask you two quick questions:Is this your first time installing OpenCV?Are you just getting started learning Linux and how to use the command line?If you answered yes to either of these questions, I highly suggest that you watch the video below and follow along with me as a guide you step-by-step on how to install OpenCV 3 with Python bindings on your Raspberry Pi 2 running Raspbian Jessie:Otherwise, if you feel comfortable using the command line or if you have previous experience using the command line, feel free to follow the tutorial below.Installing OpenCV 3 on Raspbian JessieInstalling OpenCV 3 is a multi-step (and even time consuming) process requiring you to install many dependencies and pre-requisites. The remainder of this tutorial will guide you step-by-step through

I’ll admit it: Compiling and installing OpenCV 3 on macOS Sierra was a lot more of a challenge than I thought it would be, even for someone who has a compiled OpenCV on hundreds of machines over his lifetime.If you’ve tried to use one of my previous tutorials on installing OpenCV on your freshly updated Mac (Sierra or greater) you likely ran into a few errors, specifically with the QTKit.h header files.And even if you were able to resolve the QTKit problem, you likely ran into more issues trying to get your CMake command configured just right.In order to help resolve any issues, problems, or confusion when installing OpenCV with Python bindings on macOS Sierra (or greater) I’ve decided to create two hyper-detailed tutorials:This first tutorial covers how to install OpenCV 3 with Python 2.7 bindings on macOS.My second tutorial will come next week where I’ll demonstrate how to install OpenCV 3 with Python 3.5 bindings on macOS.I decided to break these tutorials into two separate blog posts because they are quite lengthy.Furthermore, tuning your CMake command to get it exactly right can be a bit of a challenge, especially if you’re new to compiling from OpenCV from source, so I wanted to take the time to devise a foolproof method to help readers get OpenCV installed on macOS.To learn how to install OpenCV with Python 2.7 bindings on your macOS system, keep reading.The first part of this blog post details why I am creating a new tutorial for installing OpenCV 3 with Python bindings on the Mac Operating System. In particular, I explain a common error you may have run across — the QTKit.h header issue from the now deprecated QTKit library.From there, I provide super detailed instructions on how to install OpenCV 3 + Python 2.7 your macOS Sierra system or greater.Avoiding the QTKit/QTKit.h file not found errorIn the Mac OSX environment the QTKit (QuickTime Kit) Objective-C framework is used for manipulating, reading, and writing media. In OSX version 10.9 (Mavericks) QTKit was deprecated (source).However, it wasn’t until the release of macOS Sierra that much of QTKit was removed and instead replaced with AVFoundation, the successor to QTKit. AVFoundation is the new framework for working with audiovisual media in iOS and macOS.This created a big problem when compiling OpenCV on Mac systems — the QTKit headers were not found on the system and were expected to exist.Thus, if you tried to compile OpenCV on your Mac using my previous tutorials your compile likely bombed out and you ended up with an error message similar to this:fatal error: 'QTKit/QTKit.h' file not found#import ^ 1 error generated. make[2]: *** [modules/videoio/CMakeFiles/opencv_videoio.dir/src/cap_qtkit.mm.o]Error 1 make[1]: ***[modules/videoio/CMakeFiles/opencv_videoio.dir/all] Error 2 make: ***[all] Error 2Even more problematic, both the tagged releases of OpenCV v3.0 and v3.1 do not include fixes to this issue.That said, the latest commits to the OpenCV GitHub repo do address this issue; however, a new tagged release of v3.2 has yet to be released.That said, I’m happy to report that by using

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV-Python is a Python wrapper for the original OpenCV C++ library. Let’s see how it install OpenCV in python.IntroductionOpenCV enables users to perform image and video processing tasks with ease. In this blog post, we will provide a step-by-step guide on installing OpenCV-Python in various operating systems, including Windows, macOS, and Linux. We will also cover some common issues that users may encounter during the installation process.1. Pre-requisitesBefore installing OpenCV-Python, ensure that your system meets the following requirements:Python 3.6 or later installed (You can download Python from (Python Package Installer) installed with your Python distribution2. Install opencv pythonThe easiest way to install OpenCV-Python is by using pip. The commands are the same for all operating systems. Open a terminal or command prompt and enter the following command:pip install opencv-pythonTo install the package with additional contrib modules (which provide extended functionality), use:pip install opencv-contrib-python3. Verifying the Installation:Once the installation is complete, you can verify it by running a simple Python script. Open your Python IDE or create a new Python file and enter the following code:import cv2print("OpenCV-Python Version:", cv2.__version__)If the installation was successful, running the script will display the OpenCV-Python version.4. Installation on Various Operating SystemsWhile the pip command works across different platforms, there might be some OS-specific considerations when installing OpenCV-Pythona) Windows:On Windows, the process is straightforward. Just follow the steps mentioned above in 2. Installing OpenCV-Python to install OpenCV-Python using pip.b) macOS:On macOS, you may need to install additional libraries before installing OpenCV-Python. Run the following command to install Homebrew, a package manager for macOS:/bin/bash -c "$(curl -fsSL installing Homebrew, install the required libraries using the following command:brew install pkg-config libffi glibNow, proceed with the pip installation as described in 2. Installing OpenCV-Python.c) Linux:On Linux, you may need to install some additional libraries before installing OpenCV-Python. For Ubuntu/Debian-based systems, run the following command:sudo apt-get update && sudo apt-get install -y libsm6 libxext6 libxrender-devFor CentOS/Fedora-based systems, use the following command:sudo yum install libXext libSM libXrenderAfter installing the required libraries, proceed with the pip installation