karuneshpalekar/dietcompanion

The Application can be downloaded from here :

DietCompanion

It is a Pre-Release : May or may not support your device

This Project is an Android Application(Non-Production Ready).The application is implemented keeping in mind the Clean Code Principles, therefore it is built using Clean Architecutre and MVI. The main aim of this application is to help people improve their Diet. It consist of Diet Recommendation System built using Tensorflow-Lite .The Application provides an interface to Note Down Items consumed to get their Nutritional Values via Azure Cosmos DB. User will be able to keep a note of the intakes they have consumed via this application. It provides the facility to the User to capture their Images and Review them overtime to keep a note of how they have progressed over time. The same functionality is implemented using Azure Blob Storage. The application keeps security in mind by Authorizing User's using Azure's B2C. The application also provides information about various Diet's it consist of.It also makes use of AppCenter and Application Insight platform to generate database with the help of the user for making Recommendation System perform better

Tests - Complete Project Working Successfully

The application is successfully tested on Xiaomi Mi A2 Device

• Device Name : Xiaomi Mi A2
• Screen Size : 5.99 inch
• SDK : 29 (Android 10)
• Video : https://youtu.be/4ACOCBn2JtA

Articles

Articles about these following topics will be published in the upcoming time (Demand for the same might promote the urgency of the article) :

• Making A Custom Recommendation System using Tensorflow Lite and connecting it to Android Project
• Connecting Android Application to Azure Platform for Authentication via Azure Active Directory B2C.
• Connecting Android Application to Azure Storage
• Connecting Android Application to Cosmos DB