It has been said multiple times this isn't running in a VM? But it says its running an ubuntu image on windows. This is really cool, I guess I like everyone is. Linux vs Windows. Compare the two operating system's from an average user's perspective.Find out the pros and cons of Linux and Windows. In this post, we will provide step by step instructions for installing OpenCV 3 (C++ and Python) on Ubuntu. Ubuntu is different. Everything is done via repositories and it uses a dedicated update manager to update both the operating system and all of the applications installed. Ubuntu 1. 6. 0. 4: How to install Open. CVOver the past two years running the Py. Image. Search blog, I’ve authored two tutorials detailing the required steps to install Open. CV (with Python bindings) on Ubuntu. You can find the two tutorials here: However, with support of Ubuntu 1. Ubuntu 1. 6. 0. 4 set as the next LTS (with support until April 2. I thought it would be appropriate to create a new, updated Ubuntu + Open. CV install tutorial. Inside this tutorial, I will document, demonstrate, and provide detailed steps to install Open. CV 3 on Ubuntu 1. Python 2. 7 or Python 3. Furthermore, this document has been fully updated from my previous Ubuntu 1. To learn how to install Open. CV on your Ubuntu 1. Note: Don’t care about Python bindings and simply want Open. CV installed on your system (likely for C++ coding)? No worries, this tutorial will still work for you. Follow along with the instructions and perform the steps — by the end of this article you’ll have Open. CV installed on your system. From there, just ignore the Python bindings and proceed as usual. Ubuntu 1. 6. 0. 4: How to install Open. CVBefore we get into this tutorial, I want to mention that Ubuntu 1. Python 2. 7 and Python 3. The actual versions (as of 2. October 2. 01. 6) are: Python 2. Python 3. 5. 2 (can be accessed via the. Again, it’s worth repeating that Python 2. Python version used by Ubuntu. There are plans to migrate to Python 3 and use Python 3 by default; however, as far as I can tell, we are still a long way from that actually becoming a reality. In either case, this tutorial will support both Python 2. Python 3. I’ve highlighted the steps that require you to make a decision regarding which version of Python you would like to use. Make sure you are consistent with your decision, otherwise you will inevitably run into compile, linking, and import errors. Regarding which Python version you should use…I’m not getting into that argument. I’ll simply say that you should use whichever version of Python you are comfortable with and use on a daily basis. Keep in mind that Python 3 is the future — but also keep in mind that porting Python 2. Python 3 isn’t terribly challenging either once you understand the differences between the Python versions. And as far as Open. CV goes, Open. CV 3 doesn’t care which version of Python you’re using: the bindings will work just the same. All that said, let’s get started installing Open. CV with Python bindings on Ubuntu 1. Step #1: Install Open. CV dependencies on Ubuntu 1. Most (in fact, all) steps in this tutorial will be accomplished by using your terminal. To start, open up your command line and update the. Next, let’s install some developer tools. The. pkg- config package is (very likely) already installed on your system, but be sure to include it in the above. The. cmake program is used to automatically configure our Open. CV build. Open. CV is an image processing and computer vision library. Therefore, Open. CV needs to be able to load various image file formats from disk such as JPEG, PNG, TIFF, etc. In order to load these images from disk, Open. CV actually calls other image I/O libraries that actually facilitate the loading and decoding process. We install the necessary ones below. Okay, so now we have libraries to load images from disk — but what about video? Use the following commands to install packages used to process video streams and access frames from cameras. Open. CV ships out- of- the- box with a very limited set of GUI tools. These GUI tools allow us to display an image to our screen (. Key ), track mouse events (. Mouse. Callback ), and create simple GUI elements such as sliders and trackbars. Again, you shouldn’t expect to be building full- fledged GUI applications with Open. CV — these are just simple tools that allow you to debug your code and build very simple applications. Internally, the name of the module that handles Open. CV GUI operations is. The. highgui module relies on the GTK library, which you should install using the following command. Next, we install libraries that are used to optimize various functionalities inside Open. CV, such as matrix operations. We’ll wrap up Step #1 by installing the Python development headers and libraries for both Python 2. Python 3. 5 (that way you have both). Note: If you do not install the Python development headers and static library, you’ll run into issues during Step #4 where we run. If these headers are not installed, then the. Python interpreter and Python libraries. In short, the output of this section will look “empty” and you will not be able to build the Python bindings. When you get to Step #4, take the time to compare your output of the command to mine. Step #2: Download the Open. CV source. At the time of this article’s publication, the most recent version of Open. CV is. 3. 1. 0 , which we download a. O opencv. zip https: //github. Itseez/opencv/archive/3. Oopencv. ziphttps: //github. Itseez/opencv/archive/3. When new versions of Open. CV are released you can check the official Open. CV Git. Hub and downloaded the latest release by changing the version number of the. However, we’re not done downloading source code yet — we also need the opencv_contrib repository as well. O opencv_contrib. Itseez/opencv_contrib/archive/3. Oopencv_contrib. ziphttps: //github. Itseez/opencv_contrib/archive/3. Why are we bothering to download the contrib repo as well? Well, we want the full install of Open. CV 3 to have access to features (no pun intended) such as SIFT and SURF. In Open. CV 2. 4, SIFT and SURF were included in the default installation of Open. CV. However, with the release of Open. CV 3+, these packages have been moved to contrib, which houses either (1) modules that are currently in development or (2) modules that are marked as “non- free” (i. You can learn more about the reasoning behind the SIFT/SURF restructuring in this blog post. Note: You might need to expand the commands above using the “< => ” button during your copy and paste. The. . zip in the. For convenience, I have included the full URL of both the. I also want to mention that both your. If the versions numbers do not matchup, you could very easily run into compile time errors (or worse, runtime errors that are near impossible to debug). Step #3: Setup your Python environment — Python 2. Python 3. We are now ready to start configuring our Python development environment for the build. The first step is to install. Python package manager. I’ve mentioned this in every single Open. CV + Python install tutorial I’ve ever done, but I’ll say it again here today: I’m a huge fan of both virtualenv and virtualenvwrapper. These Python packages allow you to create separate, independent Python environments for each project that you are working on. In short, using these packages allows you to solve the “Project X depends on version 1. Project Y needs 4. A fantastic side effect of using Python virtual environments is that you can keep your system Python neat, tidy, and free from clutter. While you can certainly install Open. CV with Python bindings without Python virtual environments, I highly recommend you use them as other Py. Image. Search tutorials leverage Python virtual environments. I’ll also be assuming that you have both. If you would like a full, detailed explanation on why Python virtual environments are a best practice, you should absolutely give this excellent blog post on Real. Python a read. I also provide some commentary on why I personally prefer Python virtual environments in the first half of this tutorial. Again, let me reiterate that it’s standard practice in the Python community to be leveraging virtual environments of some sort, so I suggest you do the same. Once we have. virtualenv and. WORKON_HOME=$HOME/. WORKON_HOME=$HOME/. The. ~/. bashrc file is simply a shell script that Bash runs whenever you launch a new terminal. You normally use this file to set various configurations. In this case, we are setting an environment variable called. WORKON_HOME to point to the directory where our Python virtual environments live. We then load any necessary configurations from. To update your. ~/. I would recommend using. You can also use graphical editors as well, but if you’re just getting started. A more simple solution is to use the. WORKON_HOME=$HOME/. WORKON_HOME=$HOME/. After editing our. Note: Calling. . bashrc only has to be done once for our current shell session. Anytime we open up a new terminal, the contents of. Now that we have installed. Python virtual environment — we do this using the.
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