Fabify analyze uploaded photos of clothing items and provide you with recommendations for complementary pieces to complete your outfit. Whether you're looking for style inspiration or need help coordinating your wardrobe, Fabify has got you covered!
- AI Image Recognition: Fabify utilizes advanced AI image recognition technology to analyze clothing items uploaded by users.
- Outfit Suggestions: Based on the analysis of the uploaded photo, Fabify provides personalized outfit suggestions tailored to your preferences and the occasion.
- Color Coordination: The app considers color coordination to ensure that your outfit looks cohesive and stylish.
- Style Recommendations: Fabify offers recommendations based on your personal style preferences, helping you explore new fashion trends and ideas.
- Seasonal Suggestions: Whether it's summer, winter, spring, or fall, Fabify suggests outfits appropriate for the current season.
- User-friendly Interface: With a sleek and intuitive design, Fabify makes it easy for users to upload photos and receive outfit recommendations effortlessly.
To get started with Fabify, follow these simple steps:
- Clone the Repository: Clone the Fabify repository to your local machine using the following command:
https://github.com/raibove/fabify.git- Install Dependencies: Navigate to the project directory and install the necessary dependencies by running:
npm i-
Set Up Environment Variables: Create a .env file with help of .env.template and add your API key
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Start the Development Server: Run the following command to start the development server:
npm run dev- Explore Fabify: Once the development server is up and running, open your web browser and navigate to http://localhost:5173 to explore Fabify and start receiving outfit suggestions!
We welcome contributions from the community to help improve Fabify and make it even more useful for users. If you're interested in contributing, please follow these guidelines:
- Fork the repository and create a new branch for your feature or bug fix.
- Make your changes and ensure that they adhere to the coding standards and guidelines.
- Test your changes thoroughly to ensure they work as expected.
- Submit a pull request with a clear description of your changes and why they are beneficial.