Here’s the Titlecse498/2018-08/schedules/all...•Front End –Native UI iOS –Swift, iOS 11+,...

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From Students… …to Professionals The Capstone Experience Project Plan Image Recognition Annotation and Validation Mobile Application Team Whirlpool Shruti Avutapalli Jessica Clappison Jackie Li Savanna Pinkoski Jack Turak Department of Computer Science and Engineering Michigan State University Fall 2018

Transcript of Here’s the Titlecse498/2018-08/schedules/all...•Front End –Native UI iOS –Swift, iOS 11+,...

Page 1: Here’s the Titlecse498/2018-08/schedules/all...•Front End –Native UI iOS –Swift, iOS 11+, CocoaPods o Table View, Collection View, Navigation, Tab Bar, Page View, GLKit View

From Students…

…to Professionals

The Capstone Experience

Project PlanImage Recognition Annotation and Validation

Mobile Application

Team WhirlpoolShruti AvutapalliJessica Clappison

Jackie LiSavanna Pinkoski

Jack Turak

Department of Computer Science and EngineeringMichigan State University

Fall 2018

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Functional Specifications

• Image Recognition Annotation Image capture through a mobile devices

TensorFlow Lite object detectiono Annotate bounded food items via Yummly API

• Provide Valid Training Data (Validation) Gamification Mechanismo Queue-in annotation submissions at random to be verified

Validation threshold

» Above – passed on to Yummly API

» Below – manual admin review needed

• Leaderboard Promote internal (Whirlpool) competition

o Increase user annotation submissions

o Increase user verifications

*Overall objective is to provide Yummly with a vast range of data for a reliable training data set, so their system can learn and suggest meal recipes based off of food items found in users’ home. *

The Capstone Experience Team Whirlpool Project Plan Presentation 2

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Design Specifications

• Home Page Navigation between dashboards

• Image Capture and Annotation Interface Camera view & capture Text annotation w/ Yummly API

• Validation/Game Interface Provide reliable training data

• Tutorial Application walk-through

• User Stats User role, scores, & submission history

• Leaderboard Current standings

The Capstone Experience Team Whirlpool Project Plan Presentation 3

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Screen Mockup: Image Recognition & Annotation Interface (iOS)

The Capstone Experience 4Team Whirlpool Project Plan Presentation

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Screen Mockup: Android Application

The Capstone Experience 5Team Whirlpool Project Plan Presentation

Home Screen Overview User Submission Gallery Validation Game

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Technical Specifications

• External Data Yummly APIo Text fields to identify detected items

• Front End – Native UI iOS – Swift, iOS 11+, CocoaPodso Table View, Collection View, Navigation, Tab Bar, Page View, GLKit View Controllers

Android – Java, API 21+ (Lollipop)

• Back End Firebaseo Firestore – Databaseo Storage – Image Storageo Authentication – Whirlpool Domain, whitelist

TensorFlow Liteo Object detection

Use of bounding boxes

The Capstone Experience Team Whirlpool Project Plan Presentation 6

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System Architecture

The Capstone Experience Team Whirlpool Project Plan Presentation 7

Android

iOS

Firebase

TensorFlowLite

Firestore

Authentication

User Creation/Sign-In

Data Storage

Storage

Image Storage

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System Components

• Hardware Platforms Mobile Deviceso Androido Apple

• Software Platforms / Technologies Android Studio – Version 3.1.4 Xcode - Version 9.4.1 o Swift – using storyboards

Firebaseo Firestoreo Storage o Authentication

TensorFlow Lite

The Capstone Experience Team Whirlpool Project Plan Presentation 8

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Risks

• Non-Uniform Cross Platform UI Design – Medium Description : There is no simple way to ensure that the apps have extremely similar UI appearances, which could cause user confusion

and make our final product appear unprofessional.

Mitigation : Maintaining consistent collaboration between both IOS and Android team as we produce our app. The overall structureneeds to function the same even if the back-end of each app functions differently.

• Object Detection in Image – High Description : Currently there is no definitive plan for how we will detect the ingredients in any given image.

Mitigation : We have to research and implement TensorFlow Lite to help with object detection. Furthermore we can reach out to other peers who are familiar with TensorFlow Lite.

• Suboptimal System Architecture – Low Description : We can access the firebase API and can store and put data on it but we have yet to fully implement firebase

in the production of our app. We don’t know how reliable, secure, or if there are any hidden restrictions that might limit our progress.

Mitigation : Get advice/approval through client. Check that all of its capabilities match all of the all the expectations we have that it will accomplish for us.

• Substandard UI – Medium Description : We don’t want any confusion when it comes to using our app. Our UI design needs to be intuitive and user

friendly.

Mitigation : Have people outside our team test our app as we finalize it to ensure a user friendly UI.

The Capstone Experience Team Whirlpool Project Plan Presentation 9

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Questions?

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