In this tutorial you will will learn how to pip install OpenCV on Ubuntu, macOS, and the Raspberry Pi. In previous OpenCV install tutorials I have recommended compiling from source; however, in the past year it has become possible to install OpenCV via pip, Python’s very own package manager. While installing from source will give you the greatest control over your OpenCV configuration, it’s also the hardest and the most time consuming. If you’re looking for the fastest possible way to install OpenCV on your system, you want to use pip to install OpenCV (but there are a few things that may trip you up along the way, so make sure you read the rest of this guide). MacOS: Install OpenCV 3 and Python 3.5 As I mentioned in the introduction to this post, I spent last week covering how to install OpenCV 3 with Python 2.7 bindings on macOS. Many of the steps in last week’s tutorial and today’s tutorial are very similar (and in some cases identical) so I’ve tried to trim down some of the explanations for. To learn how to pip install OpenCV on your system, just keep reading. Looking for the source code to this post? Pip install opencv In the remainder of this tutorial I’ll briefly describe the OpenCV packages you can install via pip, Python’s package manager. From there, I’ll demonstrate how to pip install OpenCV on Ubuntu, macOS, and the Raspberry Pi. Finally, I’ll review some common problems you may encounter when using pip to install OpenCV. I’d like to point out an important caveat to this OpenCV installation method before we begin. The PyPi/PiWheels hosted versions of OpenCV that we’re discussing today do not include “non-free” algorithms such as SIFT, SURF, and other patented algorithms. This is a great method to install OpenCV if you need a quick environment in which you won’t need to run programs containing the non-free algorithms — if that’s not the case, you’ll need to complete a full compile of OpenCV. The two pip OpenCV packages: opencv-python and opencv-contrib-python Before we get started I want to remind you that the methods I’m coming here today are unofficial pre-built OpenCV packages that can be installed via pip — they are not official OpenCV packages released. Just because they are not official packages doesn’t mean you should feel uncomfortable using them, but it’s important for you to understand that they are not endorsed and supported directly by the official team. Ant.com video downloader for mac. Ant Downloader for Mac: Download Video from Safari, Chrome and Firefox. Internet users are fond of watching videos in various video sharing sites such as YouTube. Best Video Software for the Mac How To Run MacOS High Sierra or Another OS on Your Mac Best Graphic Design Software the Mac Stay Safe with Best Free Password Managers. ![]() All that said — there are four OpenCV packages that are pip-installable on the PyPI repository: •: This repository contains just the main modules of the OpenCV library. If you’re a PyImageSearch reader you do not want to install this package. •: The opencv-contrib-python repository contains both the main modules along with the contrib modules — this is the library I recommend you install as it includes all OpenCV functionality. •: Same as opencv-python but no GUI functionality. Useful for headless systems. •: Same as opencv-contrib-python but no GUI functionality. Useful for headless systems. Again, in the vast majority of situations you will want to install opencv - contrib - python on your system. You DO NOT want to install both opencv - python and opencv - contrib - python — pick ONE of them. How to pip install OpenCV on Ubuntu You have two options to install OpenCV on Ubuntu with pip: • Install into your system site - packages • Install into a virtual environment’s site - packages (preferred) First, install pip If you don’t have pip, you’ll need to obtain it first. $ sudo pip install opencv - contrib - python In a matter of seconds, OpenCV is ready to go in your system’s site-packages! Option B: Install OpenCV on Ubuntu into a virtual environment with pip There are huge benefits to Python virtual environments. The main benefit is that you can develop multiple projects on your system with isolated packages (many with version dependencies) without having to muddy the waters of your system. You’re also free to add and remove virtual environments as you go. Put simply: Python virtual environments are a best practice for Python development. Chances are, you should jump on the bandwagon. My tools of choice are virtualenv and virtualenvwrapper but you could choose an alternative such as venv or Anaconda (conda for short). Here’s how to install virtualenv and virtualenvwrapper, both of which will live in your system site - packages and manage each project’s virtual environment site-packages. $ sudo pip install opencv - contrib - python In a matter of seconds, OpenCV is ready to go in your system’s site-packages. Option B: Install OpenCV on macOS into a virtual environment with pip Just like managing packages is a breeze with pip. Managing projects and their dependencies is a breeze with virtual environments. You should use Python virtual environments if you’re serious about computer vision development (or any development for that matter). I don’t care what system you use (be it virtualenv, venv, or conda /Anaconda), just learn to use one and stick with it.
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