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WARDROBE GENIE🎯

Basic Details

Team Name: InnovHer

Team Members

  • Member 1: Ann Saniya Rose Thomas- SCMS School of Engineering and Technology
  • Member 2: Amrutha E J - SCMS School Of Engineering and Technology

Hosted Project Link

https://wardrobe-genie.onrender.com/

Project Description

A website where we can upload our outfit pics and then an generates suggestions

The Problem statement

Every day, countless women face the challenge of deciding what to wear, ensuring they maintain variety while avoiding outfit repetition. A common preference is that an outfit worn on one day should not be repeated the next, with a rotation spanning a week or even two, depending on the available wardrobe. The process of selecting an outfit can be time-consuming, especially when considering factors such as color coordination, weather conditions, and suitability for different occasions (such as school, college, or the workplace). With a growing number of clothing options, manually tracking previously worn outfits and planning future ones becomes difficult.

The Solution

We propose Wardrobe Genie, a smart wardrobe management website that helps users effortlessly plan their outfits. The platform allows users to upload pictures of their outfits, and an AI-powered system generates suggestions for what to wear next while ensuring variety and avoiding repetition.

Technical Details

Technologies/Components Used

For Software: Backend: Flask (Python) Frontend: HTML, CSS, JavaScript Storage: Cloudinary (for storing images) Deployment: Render (for hosting Flask app) Additional Libraries: flask_cors (for handling cross-origin requests) cloudinary (for image uploads) random (for shuffling and selecting outfits) python-dotenv (for environment variables)

#Installation

#Run

Project Documentation For Software:

Screenshots (Add at least 3)scrnshot2

! !screenshot1

!ssn3

Build Photos !InnovHer partners

!build 1

!ssn3 Project Demo

Video [Add your demo video link here] Explain what the video demonstrates

screenrecord_1.mp4

Team Contribution Amrutha EJ:FRONTEND Ann Saniya Rose Thomas:Backend

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  • Python 37.6%
  • JavaScript 30.1%
  • HTML 23.1%
  • CSS 9.2%