Instead, we use miniforge, a community package that provides a minimalistic Anaconda install and uses the conda-forge branch to install packages. One of the most popular packages to accomplish this is Anaconda, but anaconda is bloated and doesn’t always have the right packages for m1. Virtual environments are a great way to separate different dependencies if you need different versions for different projects or if you don’t want to change your system path and its dependencies. To solve this inconsistency, we use virtual environments in miniforge. On M1 this is a problem and instead we want to the arm64 versions of OpenCV and its dependencies. This means that most software is still built to run on amd64 processors so when we install OpenCV, there is a strong chance your computer, or dependency manager, tries to install an amd64 version. However, computers using arm64 processors are a very small subset compared to the billions of amd64 computers that have been around for the last 15 years.
Macs with M1 processors use the arm64 architecture which is incompatible with the amd64 architecture used by the likes of Intel and AMD. Its dependency list includes packages like ffmpeg, libgfortran, and pixman which is where the issues start, especially for the M1. OpenCV is a large library with a lot of dependencies though. It provides a large set of image manipulation tools that are very useful for processing images and image streams often for use with machine learning algorithms.
OpenCV is one of the most popular computer vision libraries.
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