👗 AI Outfit Recommender

An intelligent outfit recommendation system that suggests clothing combinations based on user preferences such as weather, occasion, style, and gender.

🔗 Live Demo: https://outfitsrecommender.streamlit.app/

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🚀 Features

• 🎯 Context-aware outfit recommendations
• 🎨 Suggested color palettes for styling
• 🧠 Explainable outputs (why the outfit works)
• 🔄 Smart fallback logic (ensures no empty results)
• 💻 Interactive UI built with Streamlit

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🧠 How It Works

The system uses a rule-based recommendation approach:

1. Takes user inputs:

   • Gender
   • Weather
   • Occasion
   • Style (Ethnic / Western)

2. Matches inputs against a structured dataset

3. Applies multi-level filtering:

   • Exact match
   • Partial match (fallback)
   • Random selection (final fallback)

4. Enhances output with:

   • Color suggestions 🎨
   • Explanation of recommendations 🧠

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🛠️ Tech Stack

• Python
• Streamlit
• CSV (Dataset)

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💡 Product Thinking

Problem

Users often struggle to quickly decide outfits that match weather, occasion, and personal style. Existing fashion recommendation systems are either too generic or lack explainability.

Goal

Build a lightweight AI-powered stylist that delivers contextual outfit recommendations while keeping the interaction simple and intuitive.

UX Decisions

• Added explainable recommendations to improve user trust
• Added fallback logic to avoid dead-end experiences
• Reduced interaction friction through minimal inputs
• Designed a clean dark UI for clarity and focus

Metrics I Would Track

• Recommendation acceptance rate
• Repeat usage frequency
• Most selected outfit categories
• User feedback sentiment

Future Improvements

• Conversational AI stylist
• Personalized wardrobe memory
• Weekly outfit planning assistant
• Image-based outfit recommendations

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📂 Project Structure

Outfits_Recommender/
│
├── app/
│ └── main.py
│
├── model/
│ └── recommender.py
│
├── data/
│ └── outfits.csv
│
├── screenshots/
│ ├── overview1.png
│ ├── overview2.png
│ ├── overview3.png
│ └── overview4.png
│
├── requirements.txt
├── runtime.txt
└── README.md

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▶️ How to Run Locally

pip install -r requirements.txt
streamlit run app/main.py