Watson和OpenCV的计算机视觉入门

Introduction to Computer Vision with Watson and OpenCV

1268 次查看
IBM
Coursera
  • 完成时间大约为 14 个小时
  • 简单(初级)
  • 英语
注:本课程由Coursera和Linkshare共同提供,因开课平台的各种因素变化,以上开课日期仅供参考

课程概况

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.

课程大纲

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 and face detection. You will then use Python and the Watson Visual Recognition API to perform image classification.

Face Detection and Image Processing using OpenCV and Python

This week, you will learn how to use the Haar Cascade classifiers for detecting eyes and faces in images. 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!

Alibaba Cloud
声明:MOOC中国十分重视知识产权问题,我们发布之课程均源自下列机构,版权均归其所有,本站仅作报道收录并尊重其著作权益。感谢他们对MOOC事业做出的贡献!
  • Coursera
  • edX
  • OpenLearning
  • FutureLearn
  • iversity
  • Udacity
  • NovoEd
  • Canvas
  • Open2Study
  • Google
  • ewant
  • FUN
  • IOC-Athlete-MOOC
  • World-Science-U
  • Codecademy
  • CourseSites
  • opencourseworld
  • ShareCourse
  • gacco
  • MiriadaX
  • JANUX
  • openhpi
  • Stanford-Open-Edx
  • 网易云课堂
  • 中国大学MOOC
  • 学堂在线
  • 顶你学堂
  • 华文慕课
  • 好大学在线CnMooc
  • (部分课程由Coursera、Udemy、Linkshare共同提供)

© 2008-2019 MOOC.CN 慕课改变你,你改变世界