Microsoft Cognitive Services for Developers: 1 Vision

Course details

Microsoft Cognitive Services opens up artificial intelligence to every developer. Cognitive Services gives us access to powerful AI algorithms that allow our apps to hear, speak, identify, and interpret information using natural methods of communication. This course explores the vision APIs, which are responsible for text and image recognition and facial detection. Instructor Sahil Malik shows you how to configure Cognitive Services and use the vision capabilities to describe, tag, and categorize images; identify clip art vs. line art; moderate content; "read" text and handwriting; and recognize facial characteristics such as age, gender, emotion, hair color and type, and more. Sahil also shows how to build a facial recognition program that can recognize people in images by comparing them to a library of known persons.

Learning objectives
Setting up the project
Writing code to describe an image
Returning multiple descriptions
Writing an analyze method
Applying tags and categories
Analyzing colors
Identifying art and adult content
Recognizing celebrities and landmarks
Handwriting and OCR
Detecting faces and emotions
Identifying people

Concepts

0. Introduction

01 - Welcome
02 - What you should know
03 - Using the exercise files

1. The Basics

04 - Introduction
05 - Set up the Node.js project
06 - Add TypeScript debugging support
07 - Add helper code and demonstrate debugging

2. Describing, Categorizing, and Tagging

08 - Provision Vision API in Azure and configure project
09 - Write code to describe an image using the Vision API
10 - Run the code to describe an image using the Vision API
11 - Returning multiple descriptions
12 - Defining the analysis business object
13 - Writing the analyze method
14 - Using the analyze method to describe an image
15 - Tags and categories

3. Performing Deeper Analysis

16 - Analyzing colors
17 - Identifying line drawing and clip art vs. real pictures
18 - Identifying adult vs. racy content
19 - Generating thumbnails

4. Working with Models

20 - Recognizing celebrities
21 - Recognizing landmarks

5. Handwriting and OCR

22 - Set up the Node.js project
23 - Submit an image for handwriting or OCR
24 - Polling for status of submitted image
25 - Synchronous treatment for OCR
26 - Performing OCR
27 - Performing handwriting recognition

6. Working with Faces

28 - Recognize faces using the Vision API
29 - Provision the Emotion API and update the project
30 - Making code changes to analyze emotions
31 - Recognizing emotions for multiple pictures
32 - Provision the Face API and update the project

7. Identifying People

33 - Recognizing faces - The theory
34 - Set up your project
35 - Set up your sample dataset
36 - Read the dataset
37 - Organize your code and explain what you need to do
38 - Create a person group
39 - Delete or train the person group
40 - Create a person and add a face
41 - Add detection and identification functions
42 - Create a person group using helper classes
43 - Train a person group
44 - Detecting and identifying a person
45 - Run code and delete the person group

Conclusion

46 - Next steps