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Vastra - Your Fashion Advisor👚

Problem Statement

• The fast fashion industry, known for its short product life cycles and low prices, is facing significant challenges due to its environmental impact, including textile waste and pollution.

• Young consumers, especially Gen Z, are increasingly conscientious about the environmental and social implications of their purchases, seeking quality and individuality in their clothing.

• Traditional fast fashion models, with their mass production and inefficient supply chains, fail to meet these expectations. This presents an opportunity for the industry to innovate by adopting environmentally friendly practices and new technologies, allowing them to address these concerns and differentiate themselves from competitors.

Solution

Vastra is an intelligent fashion advisory platform that revolutionises your online shopping experience. By leveraging advanced AI technology, Vastra provides personalized outfit suggestions that consider your skin tone and local weather conditions, ensuring you look and feel your best every day. Enhance retail sustainability and customer engagement through AI-driven analytics for personalized recommendations, augmented by machine learning for predictive insights.

• Our AI analyzes your skin tone and considers local weather data to suggest outfits that match your complexion and suit current weather conditions.

• Instead of spending time deliberating over what to wear, our platform provides instant outfit suggestions based on the weather and your personal preferences.

• By integrating with weather APIs, our system continuously updates and adapts outfit recommendations based on real-time weather forecasts.

• Machine learning adapts to your style preferences for personalized advice and learns from your past outfit choices and style preferences.

• Customized AR/VR characters enhance engagement and personalization of the fashion experience by selecting AR/VR avatars or characters that represent their style and personality.

Authors

  • Roshni Kumari
  • Antima Mishra
  • Pranjali Bhradawaj

Myntra1

Features

Personalized Outfit Recommendations

  • Skin Tone Analysis: Our AI analyzes your skin tone to suggest outfits that complement your complexion.
  • Weather-Based Suggestions: By integrating with weather APIs, our system provides outfit recommendations based on real-time weather forecasts.
  • Instant Suggestions: Save time with instant outfit suggestions tailored to the current weather and your personal preferences.

Machine Learning Adaptation

  • Learning Your Style: Our machine learning algorithms adapt to your style preferences, learning from your past outfit choices to provide increasingly accurate recommendations.
  • Personalized Advice: Get advice that reflects your unique style and preferences.

Enhanced Engagement with AR/VR

  • Customized Avatars: Enhance your fashion experience by selecting AR/VR avatars or characters that professionally represent your style and personality.
  • Immersive Fashion Experience: Engage with your fashion choices in a new and interactive way using AR/VR technology.

Objectives

  • User-Friendly Interface: Create a responsive web application with a dialogue box where users can input their preferences and receive personalized fashion advice.
  • Efficient User Experience: Provide quick and accurate responses to user queries, making the fashion selection process seamless and enjoyable.

Workplan

Myntra1

  1. User Input Handling: Receive HTTP requests with user preferences and queries.
  2. Natural Language Understanding (NLU): Analyze the intent of user inputs using NLU.
  3. Model Prediction: Use a trained LSTM neural network implemented with TensorFlow and Python to predict the best outfit suggestions.
  4. Response Generation: Generate and deliver personalized outfit recommendations.
  5. Continuous Learning: Adapt and improve recommendations based on user feedback and new data.

Deliverables

  • Interactive Dialogue Box: A user-friendly interface where users can ask for fashion advice and receive personalized responses.
  • Real-Time Recommendations: Outfit suggestions that update based on current weather conditions and user preferences.
  • Personalized Fashion Experience: A platform that learns and evolves with each user's unique style.

Installation

To set up the Vastra project locally, follow these steps:

  1. Clone the Repository:

    git clone https://github.com/yourusername/vastra.git

  2. Navigate to the Project Directory:

    cd vastra

  3. Install Dependencies:

    pip install -r requirements.txt

  4. Run the Application:

    python app.py

Contributing

We welcome contributions from the community. To contribute, please follow these steps:

  1. Fork the repository.
  2. Create a new branch.
  3. Make your changes.
  4. Submit a pull request.

We hope you enjoy using Vastra as much as we enjoyed building it! For any questions or feedback, please feel free to reach out to us.