We're through all the crucial topics that are needed to easily take on computer vision algorithms using hands-on examples and real-life scenarios. We started this chapter by learning about OpenCV and its overall structure, including its modules and main building blocks. This helped us gain a perspective of the computer vision library that we'll be working on, but, more importantly, this gave us an overview of what's possible and what to expect when dealing with computer vision algorithms in general. We moved on to learn where and how to get OpenCV and how to install or build it on our own. We also learned how to create, build, and run C++ and Python projects that use the OpenCV library. Then, by learning all about the Mat class and dealing with pixels in an image, we learned how to alter and display an image. The final sections of this chapter included everything we need to know about reading and writing images from files saved on disk, whether they are single (or multi-page) images or videos files, and also cameras and network feeds. We finished the chapter by learning about a few other types from the OpenCV Mat family that can help improve our applications.

Now that we are aware of the real nature of an image (that it is, in essence, a matrix), we can start with possible operations on matrices and matrix-like entities. In the next chapter, we're going to learn all about the matrix and array operations that fall into the realm of computer vision. By the end of the next chapter, we'll be able to perform tons of pixel-wise and image-wise operations and transformations using OpenCV.