Korede Bashir

Consumer Goods & Services

Information & Communications Technology

Transports & Logistics

Artificial Intelligence DevOps devops security azure devops security AI & Machine Learning

Lagos, Nigeria

Developing an emotion capturing app with Python on Azure

During this session, the audience would be walked through building an AI-powered web app using Python and Flask running on Microsoft Azure. This web app analyses faces using AI and stores information about the emotion of faces in the image, notifying the user if it detects sad faces multiple times. The web app also serves up a simple HTML page showing the data captured.

Once a picture has been successfully taken, a Web API - built in Python - will receive the picture, and analyze it using the Azure Face API from Azure Cognitive Services (an AI service that can recognize faces in images, as well as estimating the age of the face, if the person is smiling amongst other things).

The Web API will use this cognitive service to detect the emotion of all the faces. This will then be saved into a database called CosmosDB - a document database. These documents contain key/value pairs of data stored in a format called JSON. The API would also return a count of emotions, which the python app would use in asking wether the user is ‘Okay’ when the number of sad faces is greater than or equal to 3.

The app basically selects an emotion, and a user has to try their best to show that emotion on their face. Once they have their best emotion face on, they take a picture with a camera and the web game will check to see what emotion they are showing using the Azure Face API. If it is the same as the one they were asked to show, the app returns a success, and a failure, if otherwise.

This is a simple illustration around how this technology could be used as a self care app.


Korede Bashir

Chief Technology Officer, Bute Systems

A result-driven software engineer with expertise in community building :) // I teach Microsoft technologies - especially cloud solutions based on Microsoft Azure and Azure Stack.

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