Joseph Howse & Prateek Joshi 
OpenCV: Computer Vision Projects with Python [EPUB ebook] 

Get savvy with Open CV and actualize cool computer vision applications

• Use Open CV’s Python bindings to capture video, manipulate images, and track objects


• Learn about the different functions of Open CV and their actual implementations.


• Develop a series of intermediate to advanced projects using Open CV and Python

This learning path is for someone who has a working knowledge of Python and wants to try out Open CV. This Learning Path will take you from a beginner to an expert in computer vision applications using Open CV. Open CV’s application are humongous and this Learning Path is the best resource to get yourself acquainted thoroughly with Open CV.

• Install Open CV and related software such as Python, Num Py, Sci Py, Open NI, and Sensor Kinect – all on Windows, Mac or Ubuntu


• Apply ‘curves’ and other color transformations to simulate the look of old photos, movies, or video games


• Apply geometric transformations to images, perform image filtering, and convert an image into a cartoon-like image


• Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor


• Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques


• Detect and recognize street signs using a cascade classifier and support vector machines (SVMs)


• Identify emotional expressions in human faces using convolutional neural networks (CNNs) and SVMs


• Strengthen your Open CV2 skills and learn how to use new Open CV3 features

Open CV is a state-of-art computer vision library that allows a great variety of image and video processing operations. Open CV for Python enables us to run computer vision algorithms in real time. This learning path proposes to teach the following topics. First, we will learn how to get started with Open CV and Open CV3’s Python API, and develop a computer vision application that tracks body parts. Then, we will build amazing intermediate-level computer vision applications such as making an object disappear from an image, identifying different shapes, reconstructing a 3D map from images , and building an augmented reality application, Finally, we’ll move to more advanced projects such as hand gesture recognition, tracking visually salient objects, as well as recognizing traffic signs and emotions on faces using support vector machines and multi-layer perceptrons respectively.

This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:

• Open CV Computer Vision with Python by Joseph Howse


• Open CV with Python By Example by Prateek Joshi


• Open CV with Python Blueprints by Michael Beyeler

This course aims to create a smooth learning path that will teach you how to get started with will learn how to get started with Open CV and Open CV 3’s Python API, and develop superb computer vision applications. Through this comprehensive course, you’ll learn to create computer vision applications from scratch to finish and more!.