Indeed I prefer and use PyEnv for this and if you like you may look at another project to which I contribute. It includes many helpful information which I modified slightly leaving out the Python installation using virtualenv and virtualenvwrapper as a virtual Python environment. The article is pretty good but it is concentrating on OpenCV for Python. You can use the following procedure to build OpenCV from source code as it is also described on. This is the reason why I recommend to use install OpenCV by building it from the sources available on GitHub. The following shows the brew command to install opencv together with some of those options that was working for a long time: cuda optimized versions of the libraries that you might want to use. There is the core package as well as the so called Contrib Package that includes some more algorithms which are perhaps not released or fully tested as well as some algorithms that are patented and therefore some more difficult to use in terms of licensing. It's important to know that OpenCV has different packages. Required: ceres-solver ✔, eigen ✔, ffmpeg ✔, glog ✔, harfbuzz ✔, jpeg ✔, libpng ✔, libtiff ✔, numpy ✘, openblas ✔, openexr ✔, protobuf ✘, ✔, tbb ✔, vtk ✔, webp ✔
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