Book Image

Computer Vision Projects with OpenCV and Python 3

By : Matthew Rever
Book Image

Computer Vision Projects with OpenCV and Python 3

By: Matthew Rever

Overview of this book

Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google’s Tesseract software, and tracking human body poses using DeeperCut within TensorFlow. By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries.
Table of Contents (9 chapters)

Facial recognition

We're going to see how we can perform facial recognition with dlib with a relatively small amount of code. Facial recognition here means that we're going to look at an image and see whether or not this person is the same as the person in a different image. We're going to keep it simple here and just compare two faces to see whether they're the same, but this can easily be generalized, as we'll see later.

Here, we're going to do something similar to the first example, where we're going to prompt the user to open two files, each with a face that is going to be compared to another. For this, we are going to use some faces from Labeled Faces in the Wild (LFW). It's a nice database that has thousands of faces from various celebrities. You can download the entire set from http://vis-www.cs.umass.edu/lfw/ and get a whole lot...