Google Cloud Vision API by Example

Google Cloud Vision API by Example
Google Cloud Vision API by Example
English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 1h 09m | 191 MB

Google Cloud Vision API encapsulates powerful machine learning models in an easy-to-use REST API, allowing developers to leverage the power of machine learning without needing to train models of their own. Vision API gives you the power to annotate your images and text, detect objects and faces, automatically identify product logos and landmarks, and more. In this hands-on course, instructor Jonathan Fernandes helps you get up and running with this powerful product. Jonathan demonstrates how to make calls to the API with Python and leverage services that allow you to extract text from images, detect labels and facial expressions, and work effectively with batches of images.

Topics include:

  • Detecting text with optical character recognition
  • Navigating through the Vision API documentation
  • How the Vision API can detect facial expressions
  • Detecting and extracting multiple objects
  • Preparing data for batch images
  • Working with JSON and Pandas
Table of Contents

1 Machine learning for images made easier
2 What is Google Vision API
3 Getting started
4 Testing setup
5 Detect text with optical character recognition (OCR)
6 Detect labels
7 Working with Google Cloud Vision API documentation
8 Facial expression detection
9 Face detection
10 Detecting multiple objects
11 Challenge Determine the landmark
12 Solution Determine the landmark
13 Data preparation for batch images
14 Creating the batch image request
15 Working with JavaScript Object Notation (JSON)
16 Working with Pandas
17 Clean up
18 Next steps