- #OPENMP HELLO WORLD MAC OS X 2017 HOW TO#
- #OPENMP HELLO WORLD MAC OS X 2017 INSTALL#
- #OPENMP HELLO WORLD MAC OS X 2017 PORTABLE#
Hint: You can check if Homebrew is already installed on your machine by executing the brew command in your terminal. If you haven’t already installed Homebrew, you can do so by executing the following commands: $ /usr/bin/ruby -e "$(curl -fsSL )"
Think of Homebrew as a similar equivalent of Ubuntu’s apt-get only for macOS.
#OPENMP HELLO WORLD MAC OS X 2017 INSTALL#
In order to install Boost, Boost.Python, and CMake on macOS, you’ll be using the Homebrew package manager. I assume you already have pip (for managing, installing, and upgrading Python packages) installed on your machine, but if not, you can install pip via: $ wget Īfter completing these steps, continue to Step #2. Installing CMake, Boost, Boost.Python, and X11 can be accomplished easily with apt-get : $ sudo apt-get install build-essential cmake
#OPENMP HELLO WORLD MAC OS X 2017 HOW TO#
I’ll show you how to install each of these prerequisites on your Ubuntu or macOS machine below. The macOS/OSX version of X11 is called XQuartz.
X11/ XQuartx: Short for “X Window System”, X11 provides a basic framework for GUI development, common on Unix-like operating systems. You might already be familiar with CMake if you have used it to compile OpenCV on your system. CMake: CMake is an open-source, cross-platform set of tools used to build, test, and package software. 
Boost.Python: As the name of this library suggests, Boost.Python provides interoperability between the C++ and Python programming language. Boost provides implementations for linear algebra, multithreading, basic image processing, and unit testing, just to name a few. Boost: Boost is a collection of peer-reviewed (i.e., very high quality) C++ libraries that help programmers not get caught up in reinventing the wheel. The dlib library only has four primary prerequisites: Over the next few weeks we’ll be exploring some of these techniques (especially facial landmark detection), so definitely take the time now to get dlib configured and installed on your system. The documentation for dlib is also quite fantastic.įrom a computer vision perspective, dlib has a number of state-of-the-art implementations, including: #OPENMP HELLO WORLD MAC OS X 2017 PORTABLE#
How to install dlibĭeveloped by Davis King, the dlib C++ library is a cross-platform package for threading, networking, numerical operations, machine learning, computer vision, and compression, placing a strong emphasis on extremely high-quality and portable code. To learn how to install dlib with Python bindings on your system, just keep reading.
Face part (i.e., eyes, nose, mouth, etc.) extractionīut it all starts with getting dlib installed!. I’ll be demonstrating how to use facial landmarks for: Starting next week we’ll be diving head first into one of dlib’s core computer vision implementations - facial landmark detection. I highly encourage you to take the time to install dlib on your system over the next couple of days. Today I am going to demonstrate how to install dlib with Python bindings on both macOS and Ubuntu. Two weeks ago I interviewed Davis King, the creator and chief maintainer of the dlib library. Click here to download the source code to this post
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