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社区首页 >问答首页 >安装带有CMake 4.1.2的OpenCV 4.1.2时的OpenCV错误我从他们的github和他们的网站上安装了OpenCV和OpenCV配置4.1.2，以便在Visual中使用它们的dnn模块。我一直很难让CMake来配置和生成所需的任何东西。以下是我所犯的错误：Detected processor: AMD64libjpeg-turbo: VERSION = 2.0.2, BUILD = opencv-4.1.2-libjpeg-turboIPPICV: Download: ippicv_2019_win_intel64_20180723_general.zipfound Intel IPP (ICV version): 2019.0.0 [2019.0.0 Gold]at: C:/opencv+contrib/3rdparty/ippicv/ippicv_win/icvfound Intel IPP Integration Wrappers sources: 2019.0.0at: C:/opencv+contrib/3rdparty/ippicv/ippicv_win/iwCould not find OpenBLAS include. Turning OpenBLAS_FOUND offCould not find OpenBLAS lib. Turning OpenBLAS_FOUND offCould NOT find BLAS (missing: BLAS_LIBRARIES) LAPACK requires BLASA library with LAPACK API not found. Please specify library location.VTK is not found. Please set -DVTK_DIR in CMake to VTK build directory, or to VTK install subdirectory with VTKConfig.cmake fileCMake Error at cmake/OpenCVModule.cmake:289 (message): No modules has been found: C:/opencv_contrib-4.1.2Call Stack (most recent call first): cmake/OpenCVModule.cmake:371 (_glob_locations) modules/CMakeLists.txt:7 (ocv_glob_modules)ADE: Download: v0.1.1f.zipOpenCV Python: during development append to PYTHONPATH: C:/opencv+contrib/python_loaderFFMPEG: Download: opencv_videoio_ffmpeg.dllFFMPEG: Download: opencv_videoio_ffmpeg_64.dllFFMPEG: Download: ffmpeg_version.cmakeRegistering hook 'INIT_MODULE_SOURCES_opencv_dnn': C:/opencv/opencv/sources/modules/dnn/cmake/hooks/INIT_MODULE_SOURCES_opencv_dnn.cmakeopencv_dnn: filter out cuda4dnn source codeCMake Warning at cmake/OpenCVGenSetupVars.cmake:54 (message): CONFIGURATION IS NOT SUPPORTED: validate setupvars script in install directoryCall Stack (most recent call first): CMakeLists.txt:944 (include)我在googling中发现的另一篇文章说，Python路径可能不正确，但是当我在cmd中输入python --version时，它告诉我Python3.7.4回答 1Stack Overflow用户发布于 2019-11-29 07:33:46尝试安装vcpkg，从这里您可以下载并安装OpenCV x86和x64。但是，这里并不是所有的模块都可用。最常见的，包括DNN，见下图。​要用DNN包安装OpenCV，您需要输入以下行：X86：.\vcpkg install opencv4[dnn]X64：.\vcpkg install opencv4[dnn]:x64-windows页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持原文链接：

Introduction: Opencv and Python Installation for Windows / MacOpenCV is an open source computer vision library which is very popular for performing basic image processing tasks such as blurring, image blending, enhancing image as well as video quality, thresholding etc. In addition to image processing, it provides various pre-trained deep learning models which can be directly used to solve simple tasks at hand. The programmers have to download and load the model using OpenCV instructions in order to do the task of inference on their own dataset.Firstly, you need to install OpenCV library in your system prior to using it for your own dataset. At this stage, there can be two pathways of installing OpenCV in your system namely – (a) Using pip (b) Source Installation. pip is the package manager which is used to install the packages written in python. The difference between installing a python package from source and through pip are given in the table:Step 1: Download OpenCVStep 2: Download OpenCV-contribAs you can see in the image above, Click on Sources button to download OpenCV – 4.1.0 archive files into your system. Once the download is complete, unzip the files at your desired location. For illustration purpose, I am going to create a folder named as ‘opencv’ in my Desktop and I will unzip the downloaded archive inside the same folder.In order to download OpenCV_contrib you must open the command line tool and clone the repository by executing the following command: for windows: click on Clone /

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