Summary
In this chapter, we learned what deep learning is and how to use it on OpenCV with object detection and classification. This chapter is a foundation for working with other models and deep neural networks for any purpose.
Till now we learned how to obtain and compile OpenCV, how to use the basic image and mat operations, and how to create your own graphical user interfaces. You used basic filters and applied all of them in an industrial inspection example. We looked at how to use OpenCV for face detection and how to manipulate it to add masks. Finally, we introduced you to very complex use cases of object tracking, text segmentation, and recognition. Now you are ready to create your own applications in OpenCV, thanks to these use cases, which show you how to apply each technique or algorithm. In the next chapter, we learn to write some image processing filters for desktops and for small embedded systems such as Raspberry Pi.
