OpenCV Computer Vision with Python

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About This Book- Set up OpenCV, its Python bindings, and optional Kinect drivers on Windows, Mac or Ubuntu
- Create an application that tracks and manipulates faces
- Identify face regions using normal color images and depth imagesWho This Book Is ForThis book is written for Python developers who are new to computer vision and want a practical guide to teach them the essentials. Some knowledge of image data would be beneficial. You will need access to at least one webcam and will require a second one for certain exercises.What You Will Learn- Install OpenCV and related software, such as Python, NumPy, SciPy, OpenNI, and SensorKinect—on Windows, Mac, or Ubuntu
- Capture, display, and save photos, as well as real-time videos
- Handle window events and input events using OpenCV's HighGUI module or Pygame
- Understand OpenCV's image format and how to perform efficient operations on OpenCV images with NumPy and SciPy
- Apply an effect only to certain depths of an image by using data from a depth sensor, such as Kinect
- Track faces, eyes, noses, and mouths by using prebuilt datasets
- Apply "curves" and other color transformations to simulate the look of old photos, movies, or video gamesIn DetailOpenCV Computer Vision with Python shows you how to use the Python bindings for OpenCV. By following clear and concise examples, you will develop a computer vision application that tracks faces in live video and applies special effects to them. If you have always wanted to learn which version of these bindings to use, how to integrate with cross-platform Kinect drivers, and how to efficiently process image data with NumPy and SciPy, then this book is for you.This book has practical, project-based tutorials for Python developers and hobbyists who want to get started with computer vision with OpenCV and Python. It is a hands-on guide that covers the fundamental tasks of computer vision, capturing, filtering, and analyzing images, with step-by-step instructions for writing both an application and reusable library classes.

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