Download opencv 3 4 12

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

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

/build/opencv/src/opencv-4.5.2/modules/core/src/hal_internal.cpp: In function ‘int lapack_QR(fptype*, size_t, int, int, int, fptype*, size_t, fptype*, int*)’:/build/opencv/src/opencv-4.5.2/modules/core/src/hal_internal.cpp:293:111: error: too few arguments to function ‘void dgels_(const char*, const int*, const int*, const int*, double*, const int*, double*, const int*, double*, const int*, int*, size_t)’ 293 | dgels_(mode, &m, &n, &k, (double*)tmpA, &ldtmpA, (double*)b, &m, (double*)&work1, &lwork, info); | ^In file included from /usr/include/lapack.h:11, from /usr/include/lapacke.h:36, from /build/opencv/src/build/opencv_lapack.h:12, from /build/opencv/src/opencv-4.5.2/modules/core/src/hal_internal.cpp:51:/usr/include/lapack.h:1525:6: note: declared here 1525 | void LAPACK_dgels_base( | ^~~~~~~~~~~~~~~~~/build/opencv/src/opencv-4.5.2/modules/core/src/hal_internal.cpp:302:111: error: too few arguments to function ‘void dgels_(const char*, const int*, const int*, const int*, double*, const int*, double*, const int*, double*, const int*, int*, size_t)’ 302 | dgels_(mode, &m, &n, &k, (double*)tmpA, &ldtmpA, (double*)b, &m, (double*)buffer, &lwork, info); | ^In file included from /usr/include/lapack.h:11, from /usr/include/lapacke.h:36, from /build/opencv/src/build/opencv_lapack.h:12, from /build/opencv/src/opencv-4.5.2/modules/core/src/hal_internal.cpp:51:/usr/include/lapack.h:1525:6: note: declared here 1525 | void LAPACK_dgels_base( | ^~~~~~~~~~~~~~~~~/build/opencv/src/opencv-4.5.2/modules/core/src/hal_internal.cpp:314:114: error: too few arguments to function ‘void dgels_(const char*, const int*, const int*, const int*, double*, const int*, double*, const int*, double*, const int*, int*, size_t)’ 314 | dgels_(mode, &m, &n, &k, (double*)tmpA, &ldtmpA, (double*)tmpB, &m, (double*)&work1, &lwork, info); | ^In file included from /usr/include/lapack.h:11, from /usr/include/lapacke.h:36, from /build/opencv/src/build/opencv_lapack.h:12, from /build/opencv/src/opencv-4.5.2/modules/core/src/hal_internal.cpp:51:/usr/include/lapack.h:1525:6: note: declared here 1525 | void LAPACK_dgels_base( | ^~~~~~~~~~~~~~~~~/build/opencv/src/opencv-4.5.2/modules/core/src/hal_internal.cpp:323:114: error: too few arguments to function ‘void dgels_(const char*, const int*, const int*, const int*, double*, const int*, double*, const int*, double*, const int*, int*, size_t)’ 323 | dgels_(mode, &m, &n, &k, (double*)tmpA, &ldtmpA, (double*)tmpB, &m, (double*)buffer, &lwork, info); | ^In file included from /usr/include/lapack.h:11, from /usr/include/lapacke.h:36, from /build/opencv/src/build/opencv_lapack.h:12, from /build/opencv/src/opencv-4.5.2/modules/core/src/hal_internal.cpp:51:/usr/include/lapack.h:1525:6: note: declared here 1525 | void LAPACK_dgels_base( | ^~~~~~~~~~~~~~~~~[ 9%] Building CXX object modules/core/CMakeFiles/opencv_core.dir/src/split.dispatch.cpp.o[ 9%] Building CXX object modules/core/CMakeFiles/opencv_core.dir/src/stat.dispatch.cpp.o[ 9%] Building CXX object modules/core/CMakeFiles/opencv_core.dir/src/stat_c.cpp.omake[2]: *** [modules/core/CMakeFiles/opencv_core.dir/build.make:509: modules/core/CMakeFiles/opencv_core.dir/src/hal_internal.cpp.o] Error 1make[2]: *** Waiting for unfinished jobs....

2048. See the image below.Increase SWAP spaceOnce done, save the file (Ctrl + O, then Enter) and Exit (Ctrl + X).To apply the changes, restart the SWAP service with the commands below:sudo /etc/init.d/dphys-swapfile stopsudo /etc/init.d/dphys-swapfile startStep 6. Now, we have everything set to start compiling and installing OpenCV. Activate the virtual environment with the workon command.workon sbb_cvStep 7. Install Numpy with the pip command.pip3 install numpyInstall NumpyStep 8. With NumPy installed, we can now start configuring OpenCV. Navigate to the OpenCV directory to get started.Note: You need to be in the /opencv/build directory when executing the cmake command. You can use the pwd command to see your current working directory.cd opencvmkdir buildcd buildcmake -D CMAKE_BUILD_TYPE=RELEASE \ -D CMAKE_INSTALL_PREFIX=/usr/local \ -D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib/modules \ -D ENABLE_NEON=ON \ -D ENABLE_VFPV3=ON \ -D BUILD_TESTS=OFF \ -D INSTALL_PYTHON_EXAMPLES=OFF \ -D OPENCV_ENABLE_NONFREE=ON \ -D CMAKE_SHARED_LINKER_FLAGS=-latomic \ -D BUILD_EXAMPLES=OFF ..Configure OpenCVThe cmake command might take a couple of minutes to execute. Please be patient.Step 9. We have already configured OpenCV for installation. Now let’s start compiling with all the Four cores of the Pi. Execute the command below:make -j4This is one of the longest steps. It might take between 1 to 4 hours, depending on the Raspberry Pi board you are using. As of writing this post, Raspberry Pi 4 is the fastest.Compiling OpenCVStep 10. Once the compiling process completes without an ERROR, we can now install OpenCV. Execute the commands below:sudo make installsudo ldconfigInstall OpenCVStep 11. Since we are done with installing OpenCV, we can reset the SWAP size to 100MB. Edit the /etc/dphys-swapfile and set the value of CONF_SWAPSIZE to 100MB as described in Step 5 above. Remember to Restart the swap service with the commands below:sudo /etc/init.d/dphys-swapfile stop sudo /etc/init.d/dphys-swapfile startStep 12. To finalize our installation, we will create symbolic links of cv2 to

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