Introduction to Computer Vision with Watson and OpenCV

Por: Coursera . en: , ,

Overview

Computer Vision is one of the most exciting fields in Machine Learning and AI. It has applications in many industries such as self-driving cars, robotics, augmented reality, face detection in law enforcement agencies. In this beginner-friendly course you will understand about computer vision, and will learn about its various applications across many industries.

As part of this course you will utilize Python, Watson AI, and OpenCV to process images and interact with image classification models. You will also build, train, and test your own custom image classifiers.

This is a hands-on course and involves several labs and exercises. All the labs will be performed on the Cloud and you will be provided access to a Cloud environment completely free of charge. At the end of the course, you will create your own computer vision web app and deploy it to the Cloud.

This course does not require any prior Machine Learning or Computer Vision experience, however some knowledge of Python programming language is necessary.

Syllabus

Introduction to Computer Vision
-This short module will introduce you to the field of computer vision. We will cover the course expectations and highlight how computer vision is making an impact across various industries. You will also be introduced to the tools used in computer vision.

Image Classification with IBM Watson
-In this module, we start by introducing the topic of image classification. We will then talk about Watson Visual Recognition, an industry-leading service provided by IBM that is used for image classification. Finally, you will create your own instance of Watson Visual Recognition and will use it to upload images and perform image classification. Let's get started!

Custom Classifiers with Watson Visual Recognition
-This module delves deeper into IBM Watson's image classifiers. You will learn to create a custom classifier in your Visual Recognition Instance and will train and test your custom classifier to classify dog images into different breeds.

Image Processing using IBM Watson and Python
-This week, you will learn about image processing. You will then use Python and the Watson Visual Recognition API to perform image classification.

Image Processing using OpenCV and Python
-This week, you will learn how to use the Haar Cascade classifiers for object recognition. You will then do a variety of hands-on labs that will teach you how to perform license plate recognition using the Tesseract OCR, colour quantization, image compression, and image processing. While completing these labs, you will also learn how to use the OpenCV package in Python

Project: Building a Web-Based Computer Vision App using IBM Cloud
-In the final week of this course, you will build a computer vision app that you will deploy on the web. For the project, you will create a custom classifier, train it and connect it to your app. You will then deploy your app to the cloud for making it accessible to anyone around the globe!

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