Computer vision is rapidly expanding in many different applications as traditional techniques, such as image thresholding, filtering, and edge detection, have been augmented by deep learning methods. TensorFlow is a widely used, powerful machine learning tool created by Google. It has user configurable APIs available to train and build complex neural network model in your local PC or in the cloud and optimize and deploy at scale in edge devices.
In this chapter, you will gain an understanding of advanced computer vision concepts using TensorFlow. This chapter discusses the foundational concepts of computer vision and TensorFlow to prepare you for the later, more advanced chapters of this book. We will look at how to perform image hashing and filtering. Then, we will learn about various methods of feature extraction and image retrieval. Moving on, we will learn about visual search in applications, its methods, and the challenges we might face. Then, we will look at an overview of the high-level TensorFlow software and its different components and subsystems.
The topics we will be covering in this chapter are as follows:
- Detecting edges using image hashing and filtering
- Extracting features from an image
- Object detection using Contours and the HOG detector
- An overview of TensorFlow, its ecosystem, and installation
