From the course: OpenCV for Python Developers

Python and OpenCV

From the course: OpenCV for Python Developers

Start my 1-month free trial Buy for my team

Python and OpenCV

“

- [Instructor] This chapter is dedicated to walking through the full Python 3 and OpenCV 4 installation process. On a historical note, this course was originally created when OpenCV 3 adoption was spreading. We are now well into the era of OpenCV 4, which comes with many algorithm optimizations and modernizations. Meanwhile, Python 3 is much more widely adopted at this time as well. While this course focuses on the fundamentals which have been available for awhile, there are many new features in OpenCV in the field of computer vision, especially in machine learning applications, which are available through this library. By installing and learning the latest versions of both Python and OpenCV, you'll be equipped to better utilize updates and improvements to the library over time. If you already have OpenCV 4 and Python 3 installed, you can safely skip to the next chapter. If not, based on the system you are using, you can watch the according install video, or if you prefer to read your instructions instead, jump to the according PDF Quick Start Guide available in the exercise files under the chapter one folder. Note that if you need or want to compile OpenCV 4 from its source code yourself, even on a Mac or perhaps on another system like an embedded processor, you should watch both Linux install videos. This builds the OpenCV library from its source code, although some steps may be specific to Linux itself. If you run into troubles, you can look for help up online. Just be sure to avoid older articles talking about OpenCV 3, Python 2.7 bindings or anything that's C++ specific. Finally, if you're simply unable to perform a local install on your machine, your ultimate fallback is to use Google Colab where OpenCV is already built in. Be sure to watch the Colab video in this chapter, however, and be aware of the limitations of using Colab with this course since not all topics this course covers work well within Colab.

Contents