![]() My aim, however, is to build OpenCV so that it could be used in both C++ and Python.įurther in this blog post I am going to summarize my notes on building OpenCV 3 on Ubuntu using conda’s Python 3.6, with further symlinking of the Python extension to other conda environments. Their availability vary by operating systems and Python versions, but they are in general a pretty good reproducible solution when OpenCV is only used in Python. It is worth to mention that there exist pre-built OpenCV 3 binaries in the menpo channel on Anaconda Cloud. It especially shines on Raspberry Pies, where conda’s pre-built binaries get installed way faster than the pip-installed ones. However, in my work I mostly use conda for managing my Python environments. Such a solution worked pretty well for me, both on Linux and macOS. In particular, Adrian creates a dedicated virtualenv environment, installs NumPy in it, and builds the whole thing having this environment activated. He provides detailed description of the required steps, as well as motivation for better development practices. When it comes to building and installing OpenCV with Python support on *nix platforms, the collection of tutorials by Adrian Rosebrock is the best.
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