Download opencv 4 5 3

Author: m | 2025-04-24

3- Run the following command to check if OpenCV is installed in the activated environment: conda list opencv, 4- If OpenCV is not installed, install it using pip command: pip install opencv-python, this should install OpenCV with Python 3.10.x. 5- After the installation is complete, verify that OpenCV is installed by running the command in Download OpenCV Source Code: Click on the Download button and select the OpenCV 3.x or OpenCV 4.x package that matches your needs. Here’s a table summarizing

OE 4. OpenCV 4 opencv/opencv Wiki - GitHub

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

OE 5. OpenCV 5 opencv/opencv Wiki - GitHub

#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

Install-OpenCV-Raspberry-Pi-64-bits/OpenCV-4-5

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. 3- Run the following command to check if OpenCV is installed in the activated environment: conda list opencv, 4- If OpenCV is not installed, install it using pip command: pip install opencv-python, this should install OpenCV with Python 3.10.x. 5- After the installation is complete, verify that OpenCV is installed by running the command in Download OpenCV Source Code: Click on the Download button and select the OpenCV 3.x or OpenCV 4.x package that matches your needs. Here’s a table summarizing

OpenCV 5 opencv/opencv Wiki - GitHub

All of our prerequisites installed, so let’s grab the 3.0.0 version of OpenCV from the OpenCV repository. (Note: As future versions of OpenCV are released just replace the 3.0.0 with the most recent version number):$ cd ~$ wget -O opencv.zip unzip opencv.zipTiming: 2m 29sFor the full install of OpenCV 3 (which includes features such as SIFT and SURF), be sure to grab the opencv_contrib repo as well. (Note: Make sure your opencv and opencv_contrib versions match up, otherwise you will run into errors during compilation. For example, if I download v3.0.0 of opencv , then I’ll want to download v3.0.0 of opencv_contrib as well):$ wget -O opencv_contrib.zip unzip opencv_contrib.zipTiming: 1m 54sStep #3: Setup PythonThe first step in setting up Python for our OpenCV compile is to install pip , a Python package manager:$ wget sudo python get-pip.pyTiming: 26sI’ve discussed both virtualenv and virtualenvwrapper many times on the PyImageSearch blog before, especially within these installation tutorials. Installing these packages is certainly not a requirement to get OpenCV and Python up and running on your Raspberry Pi, but I highly recommend that you install them!Using virtualenv and virtualenvwrapper allows you to create isolated Python environments, separate from your system install of Python. This means that you can run multiple versions of Python, with different versions of packages installed into each virtual environment — this solves the “Project A depends on version 1.x, but Project B needs 4.x” problem that often arises in software engineering.Again, it’s standard practice in the Python community to use virtual environments, so I highly suggest that you start using them if you are not already:$ sudo pip install virtualenv virtualenvwrapper$ sudo rm -rf ~/.cache/pipTiming: 17sAfter virtualenv and virtualenvwrapper have been installed, we need to update our ~/.profile file and insert the following lines at the bottom of the file:# virtualenv and virtualenvwrapperexport WORKON_HOME=$HOME/.virtualenvssource /usr/local/bin/virtualenvwrapper.shYou can use your favorite editor to edit this file, such as vim , emacs , nano , or any other graphical editor included in the Raspbian Jessie distribution. Again, all you need to do is open the file located at /home/pi/.profile and insert the

opencv/CMakeLists.txt at 4.x opencv/opencv - GitHub

The latest commit to OpenCV’s GitHub we can install OpenCV on macOS Sierra and greater.The trick is that we need to use the HEAD of the repo as opposed to a tagged release.Once OpenCV 3.2 is released I’m sure the QKit to AVFoundation migration will be included, but until then, if you want to install OpenCV 3 on your macOS system running Sierra or later, you’ll need to avoid using tagged releases and instead compile and install the development version of OpenCV 3.How do I check my Mac Operating System version?To check your Mac OS version click the Apple icon at the very top-left corner of your screen in the menu then select “About this Mac”.A window should then pop up, similar to the one below:Figure 1: Checking your OS version on Mac. My machine is currently running macOS Sierra (10.12).If you are running macOS Sierra or greater, you can use this tutorial to help you install OpenCV 3 with Python 2.7 bindings.If you are using an older version of the Mac Operating System (Mavericks, Yosemite, etc.), please refer to my previous tutorials.Step #1: Install XcodeBefore we can even think about compiling OpenCV, we first need to install Xcode, a full blown set of software development tools for the Mac Operating System.Register for an Apple Developer accountBefore downloading Xcode you’ll want to register with the Apple Developer Program (it’s free). If you have an existing Apple ID (i.e., what you use to sign in to iTunes with) this is even easier. Simply provide some basic information such as name, address, etc. and you’ll be all set.From there, the easiest way to download Xcode is via the App Store. Search for “Xcode” in the search bar, select it, and then click the “Get” button:Figure 2: Selecting Xcode from the Apple App Store.Xcode will then start to download and install. On my machine the download and install process took approximately 30 minutes.Accept the Apple Developer licenseAssuming this is the first time you’ve installed or used Xcode, you’ll need to accept the developer license (otherwise, you can skip this step). I prefer using the terminal whenever possible. You can use the following command to accept the Apple Developer License:$ sudo xcodebuild -licenseScroll to the bottom of the license and accept it.Install Apple Command Line ToolsFinally, we need to install the command line tools. These tools include packages such as make, GCC, clang, etc. This is absolutely a required step, so make sure you install the command line tools:$ sudo xcode-select --installAfter you enter the command above a window will pop up confirming that you want to install the command line tools:Figure 3: Installing the Apple Command Line Tools on macOS.Click “Install” and the Apple Command Line Tools will be downloaded and installed on your system. This should take less than 5 minutes.Step #2: Install HomebrewWe are now ready to install Homebrew, a package manager for macOS. Think of Homebrew as similar equivalent to apt-get for Ubuntu and Debian-based systems.Installing Homebrew is simple. Simply

opencv/cmake/OpenCVDownload.cmake at 4.x opencv/opencv

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

opencv/LICENSE at 4.x opencv/opencv - GitHub

For a number of different reasons, you might want/need to build OpenCV from scratch instead of using the pre-built and official libraries provided by OpenCV. Since you’ve ended up reading this post, there’s a good chance that you already know why you might need to do this, but if you don’t, you can check out my similar post from a couple of years ago for some answers on this. That post was based on OpenCV 3.3 which is considered out-of-date these days, especially with OpenCV 4 out in the market (OpenCV 4.0.1 at the time of writing this article), so I decided to write a new tutorial to address some of the differences. So without without further ado, here we go. Please note that this tutorial is written with Windows users in mind but you should be able to build with “almost” the same steps under Linux and macOS as well. You just need to convert the steps with MinGW to default make command in Linux/Unix.First things first, the prerequisites for building OpenCV 4.x for Android are:OpenCV 4.x source codes of course (You can get them here in a zip file if you choose sources instead of pre-built binaries or you can clone then from here, I’ll use OpenCV 4.0.1 just for reference)CMake (Get the latest version from CMake website, I’ll use CMake 3.13.3)Get MinGW (If you’re a Qt fan and you want to use it for building Android app, Qt installer includes MinGW by default so you can use that one, otherwise refer to the official MinGW website to get it)Android Studio (It’s available here, download the latest version available.)Use SDK manager in Android Studio to get the latest Android SDK and NDKImportant note for OpenCV version 4.0.1 prerequisites: You’ll need Android NDK Revision 16b for properly building this. 3- Run the following command to check if OpenCV is installed in the activated environment: conda list opencv, 4- If OpenCV is not installed, install it using pip command: pip install opencv-python, this should install OpenCV with Python 3.10.x. 5- After the installation is complete, verify that OpenCV is installed by running the command in Download OpenCV Source Code: Click on the Download button and select the OpenCV 3.x or OpenCV 4.x package that matches your needs. Here’s a table summarizing

History for OpenCV 5 opencv/opencv Wiki - GitHub

Google Colab ✓ Run all code examples in your web browser — works on Windows, macOS, and Linux (no dev environment configuration required!) ✓ Access to centralized code repos for all 540+ tutorials on PyImageSearch ✓ Easy one-click downloads for code, datasets, pre-trained models, etc. ✓ Access on mobile, laptop, desktop, etc. Click here to join PyImageSearch University SummaryIn this lesson we learned how to install OpenCV 3 with Python 2.7 and Python 3 bindings on your Raspberry Pi 2 running Raspbian Jessie. I provided timings for each step so ensure you can plan your install accordingly.It’s also worth mentioning that I provide OpenCV v2.4 and v3 install instructions for Raspbian Wheezy in the following posts: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.If you run into any issues during the installation process, please see the Troubleshooting section above. Additionally, I would suggest watching the video tutorial at the top of this post to aid you in the setup process.Before you go…I tend to cover a lot of great computer vision projects using OpenCV and the Raspberry Pi, so consider entering your email address in the form below to be notified when these posts go live! Join the PyImageSearch Newsletter and Grab My FREE 17-page Resource Guide PDF Enter your email address below to join the PyImageSearch Newsletter and download my FREE 17-page Resource Guide PDF on Computer Vision, OpenCV, and Deep Learning. -->

Learning OpenCV 4 Computer Vision with Python 3

Star (13) You must be signed in to star a gist Fork (4) You must be signed in to fork a gist Clone this repository at <script src=" Save SSARCandy/fc960d8905330ac695e71e3f3807ce3d to your computer and use it in GitHub Desktop. Clone this repository at <script src=" Save SSARCandy/fc960d8905330ac695e71e3f3807ce3d to your computer and use it in GitHub Desktop. Setting up OpenCV(+extra modules) with Cmake step by step tutorial Setting up OpenCV with Cmake GUIDownload OpenCV and CmakeBuild opencv with cmakePress configure, choose visual studio 2015, finishThen press generateOpen OpenCV.sln under build/Build it using Debug, Releaseright click > buildswitch to Release mode and build again[Windows] Setting up environment variableadd /bin into PATHadd new env named OpenCV_DIR, value as /buildit may need logout to apply setting, you can check it by echo %PATH%, echo %OpenCV_DIR%Build with EXTRA MODULESIn step 2. Build opencv with cmake, press configureSet up OPENCV_EXTRA_MODULES_PATH to proper path(/modules)Press configure again, then generateTo see more details instructions, see opencv_contrib READMETravis.yml examplelanguage: - cppcompiler: - gcc before_install: - sudo apt-get updateinstall: # OpenCV dependencies - Details available at: - sudo apt-get install -y build-essential - sudo apt-get install -y cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev - sudo apt-get install -y python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev # Download v3.1.0 .zip file and extract. - curl -sL > opencv.zip - unzip opencv.zip # Download EXTRA MODULES and extract. - curl -sL > opencv_contrib.zip - unzip opencv_contrib.zip # Create a new 'build' folder. - cd opencv-3.1.0 - mkdir build - cd build # Set build instructions for Ubuntu distro. - cmake -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-3.1.0/modules CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_OPENGL=ON .. # Run 'make' with four threads. - make -j5 # Install to OS. - sudo make install # Add configuration to OpenCV to tell it where the library files are located on the file system (/usr/local/lib) - sudo sh -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf' - sudo ldconfig - echo "OpenCV installed." # We need to return to the repo "root" folder, so we can then 'cd' into the C++ project folder. - cd ../../script: - cmake CMakeLists.txt - make - ./a.out. 3- Run the following command to check if OpenCV is installed in the activated environment: conda list opencv, 4- If OpenCV is not installed, install it using pip command: pip install opencv-python, this should install OpenCV with Python 3.10.x. 5- After the installation is complete, verify that OpenCV is installed by running the command in

How to install Python 3 and Opencv 4 on Windows

对于安装opencv有的人一次就成功，而有人安装了N多次才成功。我就是那个安装了N多次的人，每次遇到了很多安装错误，只能通过到网上搜教程资料，解决方法；通过一次次的试错，最终完成了安装。再此提醒第一次安装或则安装失败没有头绪的小伙伴，请注重官方安装教程： 18.04安装的opencv版本为3.4.1（其他版本也行，安装过程类似）opencv安装的依赖包有：Required PackagesGCC 4.4.x or laterCMake 2.8.7 or higherGitGTK+2.x or higher, including headers (libgtk2.0-dev)pkg-configPython 2.6 or later and Numpy 1.5 or later with developer packages (python-dev, python-numpy)ffmpeg or libav development packages: libavcodec-dev, libavformat-dev, libswscale-dev[optional] libtbb2 libtbb-dev[optional] libdc1394 2.x[optional] libjpeg-dev, libpng-dev, libtiff-dev, libjasper-dev, libdc1394-22-dev[optional] CUDA Toolkit 6.5 or higher1 首先更新数据1 sudo apt-get update2 sudo apt-get upgrade2 安装依赖包1 sudo apt-get install build-essential2 sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev3 sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev3 下载openc3.4.1数据包 解压sudo unzip opencv-3.4.1.zip5 使用CMAKE安装opencv安装时要注意你所在目录进入文件夹，创建BUILD文件夹，进入BUILD文件夹1 cd opencv-3.4.12 mkdir build3 cd build设置cmake编译参数，或者直接编译使用默认参数[option] sudo cmake -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_OPENGL=ON ..其他安装选项请参考官网教程：编译过程可能时间较长，也可能会出现编译错误而无法进行。6 进行MAKE创建编译后面的参数-j7 表示的是使用7核进行编译，而它的服务器有10核20个线程；所有可以使用更更多的核进行编写操作，这样速度会快一些。build的指令运行也同样时间会比较长。7 成功后，进行安装在此如果你未出现错误，说明你已经安装好了opencv库，但还需要配置环境。8 配置环境在配置之前，由于修改系统配置文件需要权限，请将身份转变成root修改opencv.conf文件sudo gedit /etc/ld.so.conf.d/opencv.conf文本可能为空白，在文本里添加opencv库的安装路径保存，若无法保存请确定你的身份root；关闭后，会出现警告无需担心。更新系统共享链接库再修改bash.bashrc文件sudo gedit /etc/bash.bashrc在末尾加入1 PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig 2 export PKG_CONFIG_PATH 保存退出，然后执行如下命令使得配置生效在此就已经完成配置验证是否配置成功查看opencv版本pkg-config --modversion opencv9 编辑测试程序，测试是否安装成功opencv_demo.cpp 1 #include 2 #include 3 4 using namespace std; 5 using namespace cv; 6 7 int main(void) 8 { 9 Mat src_image_ = imread("test.jpg"); // 读取当前目录下的test.jpg图片，如果保存请使用绝对路径10 imshow("src_image_", src_image_); // 打开图片文件11 waitKey(5000); // 停留5秒钟12 13 return 0;14 }CMakeLists.txt文件1 cmake_minimum_required(VERSION 3.5)2 project(test1)3 set(CMAKE_CXX_STANDARD 11)4 set(CMAKE_CXX_STANDARD_REQUIRED ON)5 6 add_executable(${PROJECT_NAME} opencv_demo.cpp)7 target_link_libraries(${PROJECT_NAME} opencv_core opencv_highgui opencv_imgcodecs)运行程序1 mkdir build # 创建目录2 cd build # 进入目录3 cmake .. # cmake自动查找父目录下的CMakeLists.txt文件4 make # 编译生成test1可执行文件5 ./test1 # 运行可执行文件, 至于代码中打开的图片是相对于test1可执行文件的相对路径如果运行成功，则安装成功；若出现编译错误请到网上搜索错误原因和解决方式。