Book Image

Advanced Computer Vision Projects [Video]

By : Matthew Rever
Book Image

Advanced Computer Vision Projects [Video]

By: Matthew Rever

Overview of this book

<p>Python’s wealth of powerful packages along with its clear syntax make state-of-the art computer vision and machine learning accessible to developers with a variety of backgrounds. This video course will equip you with the tools and skills to utilize the latest and greatest algorithms in computer vision, making applications that weren’t possible until recent years.</p> <p>In this course, you’ll continue to use TensorFlow and extend it to generate full captions from images. Later, you’ll see how to read text from license plates from real-world images using Google’s Tesseract Software. Finally, you’ll see how to track human body poses using “DeeperCut” within TensorFlow.</p> <p>At the end of this course, you’ll develop an application that can estimate human poses within images and will be able to take on the world with best practices in computer vision with machine learning.</p> <p>The code bundle for this video course is available at -&nbsp;<a href="https://github.com/PacktPublishing/Advanced-Computer-Vision-Projects" target="_blank">https://github.com/PacktPublishing/Advanced-Computer-Vision-Projects</a></p> <h1>Style and Approach</h1> <p>A project-based approach that will enable you to rapidly deploy advanced machine learning computer vision solutions in your work.</p>
Table of Contents (3 chapters)
Chapter 3
Human Pose Estimation with TensorFlow
Content Locked
Section 3
Multi-Person Pose Detection
In this video, we run a more advanced model to count the number of people and extract poses from more complex images. - Run more advanced ArtTrack model - Apply to model to multiperson images - Visualize the results