Explore Python’s powerful tools for extracting data from images and videos
About This Video
- Build powerful computer vision tools in Python with clear and concise code
- Discover deep learning methods that can be applied to a wide variety of problems in computer vision
- Crisp videos that take you directly to a practical approach to solving real-world examples
The Python programming language is an ideal platform for rapidly prototyping and developing production-grade codes for image processing and computer vision with its robust syntax and wealth of powerful libraries.
This video course will start by showing you how to set up Anaconda Python for the major OSes with cutting-edge third-party libraries for computer vision. You’ll learn state-of-the-art techniques to classify images and find and identify humans within videos.
Next, you’ll understand how to set up Anaconda Python 3 for the major OSes (Windows, Mac, and Linux) and augment it with the powerful vision and machine learning tools OpenCV and TensorFlow, as well as Dlib. You’ll be taken through the handwritten digits classifier and then move on to detecting facial features and finally develop a general image classifier.
By the end of this course, you’ll know the basic tools of computer vision and be able to put it into practice.
The code bundle for this video course is available at - https://github.com/PacktPublishing/Computer-Vision-Projects-with-Python-3
Table of Contents
- Chapter 1 : Introduction and Tool Setup
- Chapter 2 : Handwritten Digit Recognition with scikit-learn and TensorFlow
Chapter 3 : Facial Feature Tracking and Classification with dlib
- Introducing dlib 00:03:05
- What Are Facial Landmarks? 00:04:13
- Example One – Finding 68 Facial Landmarks in Images 00:11:26
- Example Two – Faces in Videos 00:05:47
- Example Three – Facial Recognition 00:09:54
- Chapter 4 : Deep Learning Image Classification with TensorFlow
- Title: Computer Vision Projects with Python 3
- Release date: June 2018
- Publisher(s): Packt Publishing
- ISBN: 9781788835565