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StyleMeApp

By Snotor

Snotor Img

    About

  • location

    Location

    London, UK

  • industry

    Industry

    Other Industries

  • expertsie

    Expertise

    UX/UI Design Custom Software Development Mobile App Development Application Testing
  • date

    Date

    12-2022 - 03-2023

Description

Style Me App is a digital wardrobe in the phone that allows users to create outfit combinations using the existing clothes, share it with their friends and get ideas on how to mix and match the items to create great outfits. The application consists of camera mode, AI background deletion, wardrobe, calendar with outfits panning, wardrobe analysis, and profile directories. Application helps to see the impact of user’s consumption on the environment.

Challenge

  • Image processing and automatic background deletion: Implementing the logic for automatic background deletion in images required accurate and efficient image processing algorithms to accurately identify and remove the background while preserving the foreground object (clothes) without any artifacts or distortions, and finding a solution that meets the criteria of high accuracy and performance.
  • Integrating with external APIs and services: The app consists of registration and login functionality via Facebook, Google and Apple, as well as using Sendgrid for password recovery. Integrating with external APIs and services, such as social media platforms and email services required understanding and adhering to their API documentation, handling authentication and authorization, and handling errors and exceptions.
  • User-friendly iOS and Android interfaces: Designing and implementing user-friendly interfaces for both iOS and Android platforms required understanding the platform-specific design guidelines, accommodating for different screen sizes, resolutions, and aspect ratios, and ensuring consistent and smooth user experiences across different devices and platforms.
  • Performance and scalability: The app has the app architecture for future AI features and high loading performance. Ensuring that the app is optimized for performance, scalability, and adaptability required designing efficient algorithms, optimizing database queries, handling large amounts of data, and planning for future feature integrations and updates.
  • Privacy and security: The app deals with sensitive user information, such as registration data, images of clothes, and social media integrations. Ensuring the privacy and security of user data required implementing proper authentication and authorization mechanisms, encrypting sensitive data, protecting against potential security vulnerabilities, and complying with relevant data privacy regulations.
  • Testing and debugging: Ensuring the quality and stability of the app through thorough testing and debugging required testing various scenarios, edge cases, and user interactions to identify and fix potential issues and bugs.

Solutions

Registration and login: Users should be able to register and create an account using their name, surname, username, email, and password. They should also be able to log in to the app using their username and password, or through social media platforms like Facebook, Google and Apple.

Forgot password functionality: The app should provide a password recovery mechanism to allow users to reset their password if they forget it.

Onboarding tutorial: The app should have an onboarding tutorial to help users understand how to use the app and its features effectively.

Camera mode and image uploading: Users should be able to use the camera mode to capture images of their clothes or upload images from their device’s gallery to add to their wardrobe with the ability of automatic background deletion.

Tagging, categorizing, and filtering functionality: Users should be able to add tags and categories to their clothes to organize them, and use search and filtering functionality to easily find specific items in their wardrobe.

Wardrobe management: Users should be able to view, edit, and delete items in their wardrobe, including adding new items, updating item details, and removing items they no longer want.

Outfit creation and management: Users should be able to create outfits by selecting items from their wardrobe, and view, edit, and delete outfits they have created. They should also be able to share their wardrobe with their friends and create outfits for each other, and grant or revoke access to their wardrobe and outfits.

Profile management: Users should be able to edit their profile information, including avatar, name, surname, and password.

Support and privacy policy: The app should provide support contact information and have a privacy policy in place to ensure the privacy and security of user data.

Account deletion: Users should be able to delete their account and associated data from the app if they choose to do so.

Outfit planning with calendar: Users should be able to plan and organize their outfits using a calendar feature, allowing them to schedule and track their outfits for different occasions or events.

Notifications: The app should provide notifications to users for important events, such as new outfit suggestions or planned outfits reminders.

Wardrobe analysis with visualization: Users should be able to view a full analysis of their wardrobe, including visualizations such as charts or graphs, that provide insights on various aspects such as colors, materials, brands, sizes, most and least worn items, and usage in outfits. This analysis should help users make informed decisions about their clothing choices and optimize their wardrobe.

Consumption behavior calculation on the environment: The app should be able to calculate and provide users with insights on their consumption behavior’s impact on the environment, including factors such as money spent, water usage, CO2 emissions, and textile waste generated due to their clothing choices. This information can help users make more sustainable and environmentally-friendly decisions in their wardrobe management.

Impact

We developed an app that allows users to create outfit combinations using the existing clothes. The application includes a camera mode, AI background deletion, wardrobe, calendar with outfit panning, wardrobe analysis, and profile directories. 

The application helps to see the impact of users’ consumption on the environment.

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