shreyasanap / myntra-weforshe

Myntra - Ecommerce Website🤠

Our project aims to revolutionize the online shopping experience by creating an intelligent fashion recommendation system that pairs tops with appropriate bottoms. Our solution ensures that customers find the perfect match, enhancing their shopping journey with ease and style.

🎯 Project Goals

1. Empower Women Shoppers: Provide a seamless and personalized shopping experience for women.
2. Increase Conversion Rates: Improve product pairing suggestions to boost sales.
3. Leverage AI and ML: Utilize advanced algorithms to recommend outfits that suit individual preferences and styles.
4. User-Friendly Interface: Create an intuitive and attractive interface that engages users.

🚀 Features

• Daily Fit Wardrobe: Recommends outfits based on weather conditions.
• Image Processing: Upload photos to see which clothes suit you best.
• Giveaway Platform: Influencers can organize fashion giveaways for customers.
• Popularity-Based Recommendations: Suggests products based on ratings and popularity.
• Collaborative Filtering: Uses K-Nearest Neighbors (KNN) for user-based recommendations.
• Content-Based Filtering: Recommends similar products using TF-IDF Vectorizer and Cosine Similarity.

🛠️ Tech Stack

• Programming Language: Python
• Libraries: NumPy, Pandas, Seaborn, Matplotlib, Scikit-Learn, NLTK
• Machine Learning: TensorFlow, Keras, Scikit-Learn
• Data Processing: Pandas, NumPy
• File Handling: Pickle
• 3d Product Display: 3 JS

📂 Project Structure

Myntra-WeForShe/
├── assets/               # Images and other assets
├── backend/              # Backend server and API
│   ├── server.py
├── frontend/             # Frontend application
│   ├── index.html
├── models/               # Machine learning models
├── data/                 # Dataset for training models
├── README.md             # Project documentation
└── package.json          # Project dependencies

👩‍💻 Usage

To clone the repository, run:

git clone https://github.com/shreyasanap/Myntra-WeforShe.git
cd Myntra-WeforShe

💭 Install Dependencies:

Go inside the cloth-recommendation folder
1. pip install sk-learn
2. pip install nltk

💡Run the Application:

1. run index.html (Inside the LandingPage folder)
2. start the server : *python server.py* (Inside the TryOn)
3. *streamlit run app.py* (Inside the Cloth-Recommendation folder)

🤝 Contributing

We welcome contributions to enhance this project. Please follow these steps:

• Fork the repository.
• Create a new branch (git checkout -b feature-branch).
• Make your changes and commit them (git commit -m 'Add new feature').
• Push to the branch (git push origin feature-branch).
• Create a pull request.

Additional Stuff 🏝️:

1. You have put these drive file inside the Cloth-Recommendation folder in order to run this cloth recommendation as these files are too large to put on github https://teensy.tech/additional