If you are looking for the latest setup of OpenCV for windows, then you have visited at the right place. From this page you can get the latest setup. The setup is supporting Windows 32 & 64-bit. OpenCV is a free and open source library that provides a wide range of computer vision algorithms.
How it works?
It is used by companies, research groups and governmental bodies around the world. It has C++, Python, Java, and MATLAB interfaces and is supported on Windows, Linux, Android, and macOS. It is heavily used in real-time applications and can take advantage of CUDA and OpenCL to accelerate some algorithms (e.g. 2D convolution).
Using pre-built binaries is the fastest way to get a Python OpenCV environment up and running. They include a built cv2 module which you can import by entering ‘import cv2’ into your Python interpreter. Prebuilt binaries support Python 2 only – if you want to use Python 3 or add non-standard features/modules you will need to build OpenCV from source.
How to use
If you do want to build from source, first download the OpenCV source files and extract them in a directory of your choice. Next you need to install the CMake tool, which simplifies the build process and can be obtained from the downloads section of the OpenCV website. Once you have done this, open the CMake GUI and select your OpenCV build directory. This is usually ‘C:OpenCV2.2’ but you can change this to anything that makes sense for your setup.
In the GUI you should see a list of all the available options for your build. The ones of interest are BUILD_PERF_TESTS and the python bindings. Ensure that these are checked and then press the Configure button.
If all goes well you should be able to push the Generate button. At this point you will have both a Release and Debug build of your project. The Release build will contain the final binary, and the Debug builds will contain all the source code and dll’s to allow you to run your application with debugging enabled.
Once your build has finished, you can open the generated solution in your IDE of choice. Depending on how many options you have checked, the solution may be quite large so be patient at this stage. Alternatively, you can simply select the solution file and copy/paste it into your project.
To check that everything has been installed correctly, you can import the cv2 module from Python. If you are using an IDE which supports debugging, this will be the fastest way to find out if the cv2 module has been built and linked successfully.
Note that some changes have been made to the cv2 module hierarchy, which means that programs written with earlier versions of OpenCV will not work. Refer to the next section, Migration & Changes, for details on how to modify your programs to work with the new modules.
Also, be sure to read the section on Building a Python Interface to OpenCV for more information on how to build and run a Python wrapper to the cv2 library. This wrapper is the easiest way to test your Python code with a functioning OpenCV library.