Book Image

Learning OpenCV 4 Computer Vision with Python 3 - Third Edition

By : Joseph Howse, Joe Minichino
Book Image

Learning OpenCV 4 Computer Vision with Python 3 - Third Edition

By: Joseph Howse, Joe Minichino

Overview of this book

Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You’ll be able to put theory into practice by building apps with OpenCV 4 and Python 3. You’ll start by understanding OpenCV 4 and how to set it up with Python 3 on various platforms. Next, you’ll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. From taking you through image processing, video analysis, and depth estimation and segmentation, to helping you gain practice by building a GUI app, this book ensures you’ll have opportunities for hands-on activities. Next, you’ll tackle two popular challenges: face detection and face recognition. You’ll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you’ll develop your skills in 3D tracking and augmented reality. Finally, you’ll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age. By the end of this book, you’ll have the skills you need to execute real-world computer vision projects.
Table of Contents (13 chapters)

Tracking pedestrians

Up to this point, we have familiarized ourselves with the concepts of motion detection, object detection, and object tracking. You are probably anxious to put this newfound knowledge to good use in a real-life scenario. Let's do just that by tracking pedestrians in a video from a surveillance camera.

You can find a surveillance video inside the OpenCV repository at samples/data/vtest.avi. A copy of this video is located inside this book's GitHub repository at chapter08/pedestrians.avi.

Let's lay out a plan and then implement the application!

Planning the flow of the application

The application will adhere to the following logic:

  1. Capture frames from a video file.
  2. Use the first 20 frames...