System Requirements Document (SRD)

mossy-authentication

1. Introduction

The mossy-authentication project is a user-centric application designed to simplify wardrobe management, outfit matching, and virtual try-ons. This document outlines the system requirements for the project, ensuring a clear roadmap for development and implementation.

The primary goal is to create a scalable MVP (Minimum Viable Product) that prioritizes virtual outfit try-ons and wardrobe management while maintaining makeup recommendations as a distinct, secondary feature.

This document has been tailored for Dev Barai in India, considering locale-specific defaults like time zones (IST) and user preferences for modern, minimalistic design.

2. System Overview

The mossy-authentication system will provide users with a seamless experience for managing their wardrobe, matching outfits, and virtually trying on clothing. The system will include:

• User Authentication: Secure login via Google and phone number.
• Wardrobe Management: Users can add, view, and manage clothing items.
• Outfit Matching System: Suggests matching items based on color logic and user preferences.
• Virtual Try-On: Allows users to upload photos and preview selected outfits using AI models.
• Makeup Recommendations: Suggests complementary makeup options based on outfit colors, displayed as a separate feature.

The system will be built with scalability in mind, leveraging modern technologies like Firebase, AI models, and clean architecture principles.

3. Functional Requirements

User Authentication

• As a User, I should be able to log in using Google or my phone number.
• As a System, I must ensure that each user has a unique ID.
• As a System, I must store user data securely in Firestore.

Wardrobe Management

• As a User, I should be able to add clothing items to my wardrobe.
• As a User, I should be able to specify the type, color, and optionally upload an image for each item.
• As a System, I must store wardrobe data under the structure users/{userId}/wardrobe/.

Outfit Matching System

• As a User, I should be able to select a clothing item and see matching suggestions from my wardrobe.
• As a System, I must use color-matching logic to suggest items (e.g., black → white, grey, blue).
• As a System, I must only suggest items that exist in the user's wardrobe.

Outfit Suggestion Screen

• As a User, I should see a list of matching outfits with labels like "Best Match," "Casual," and "Formal."

Virtual Try-On

• As a User, I should be able to upload a photo of myself.
• As a System, I must generate a preview image of the user wearing the selected outfit using AI models like VITON or Stable Diffusion.

Makeup Recommendations

• As a User, I should receive makeup suggestions based on my outfit colors.
• As a System, I must display makeup recommendations separately from the wardrobe and outfit matching features.

4. User Personas

1. User:

   • Primary user of the app.
   • Can log in, manage wardrobe, view outfit suggestions, and use the virtual try-on feature.
   • Receives makeup recommendations as an optional feature.

2. Admin (Future Scope):

   • Manages backend operations, monitors user activity, and ensures system integrity.

5. Visuals Colors and Theme

Unique Color Palette for mossy-authentication:

• Background: #F5F7FA (Soft Mist White)
• Surface: #FFFFFF (Pure White)
• Text: #2C2E3E (Deep Slate)
• Accent: #6C63FF (Violet Glow)
• Muted Tones: #A3A3A3 (Soft Gray)

This palette reflects a clean, modern aesthetic with a focus on simplicity and usability.

6. Signature Design Concept

Interactive Wardrobe Carousel

The homepage will feature an Interactive Wardrobe Carousel as its centerpiece. Users will see a rotating 3D carousel of their wardrobe items, categorized by type (e.g., shirts, pants, dresses).

• Animations:

  • Items will smoothly rotate in 3D as users swipe left or right.
  • Hovering over an item will enlarge it slightly, revealing details like type, color, and an optional image.

• Transitions:

  • Clicking on an item will trigger a zoom-in animation, transitioning to the outfit suggestion screen.

• Micro-Interactions:

  • Subtle haptic feedback on mobile devices when selecting or swiping items.
  • A glowing outline around the "Best Match" items in the carousel.

This bold, dynamic design will make the app feel engaging and intuitive, leaving a lasting impression on users.

7. Non-Functional Requirements

• Performance: The app must load within 2 seconds on a standard 4G connection.
• Scalability: The system must support up to 1 million users without performance degradation.
• Security: User data must be encrypted both in transit and at rest.
• Accessibility: The app must comply with WCAG 2.1 Level AA standards.
• Localization: Default to English (India) with support for additional languages in the future.

8. Tech Stack

• Frontend:

  • React for Web
  • React Native for Mobile

• Backend:

  • Python
  • FastAPI

• Database:

  • Firestore for user and wardrobe data
  • MySQL for structured data (future scalability)

• AI Models:

  • VITON or Stable Diffusion for virtual try-on
  • GPT 5.4 for user-friendly responses

• AI Tools:

  • Litellm for LLM Routing
  • Langchain

• Orchestration:

  • Docker and docker-compose for local development
  • Kubernetes for server-side orchestration

9. Assumptions and Constraints

Assumptions

• Users will have access to a stable internet connection.
• Users will upload high-quality images for the virtual try-on feature.
• The app will initially target Android and iOS platforms.

Constraints

• Virtual try-on accuracy depends on the quality of AI models and user-uploaded images.
• Firebase Firestore will be used for MVP, with potential migration to MySQL for scalability.

10. Glossary

• MVP: Minimum Viable Product.
• Firestore: A NoSQL cloud database by Firebase.
• VITON: Virtual Try-On Network, an AI model for generating outfit previews.
• WCAG: Web Content Accessibility Guidelines.
• LLM: Large Language Model.