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Try on virtual clothes
HR VITON Streamlit

HR VITON Streamlit

Generate clothes try-on images using custom clothes and poses

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What is HR VITON Streamlit ?

HR VITON Streamlit is a web-based application built using Streamlit, designed to enable users to virtually try on clothes. It leverages advanced AI technology to generate high-quality images of custom clothing items on virtual models, allowing users to explore different outfits and poses. The app is user-friendly and integrates seamlessly with your browser, making it accessible for both casual users and fashion professionals.

Features

• Virtual Try-On: Upload custom clothes and see how they look on virtual models.
• Custom Clothing Upload: Supports various clothing formats for personalized styling.
• Pose Adjustment: Adjust the model's pose to match your desired look.
• Real-Time Preview: See the results instantly as you make changes.
• User-Friendly Interface: Intuitive design for easy navigation and customization.
• Shareability: Download or share your virtual try-on results effortlessly.

How to use HR VITON Streamlit ?

  1. Install Streamlit: Ensure you have Streamlit installed in your environment.
  2. Clone the Repository: Download the HR VITON Streamlit codebase from the repository.
  3. Run the App: Execute the Streamlit script to launch the application in your browser.
  4. Upload Clothes: Select and upload your custom clothing images.
  5. Adjust Settings: Modify poses or other parameters to achieve your desired outcome.
  6. Generate Results: Click the generate button to create the virtual try-on image.
  7. Share or Download: Save or share the generated image as needed.

Frequently Asked Questions

What are the system requirements to run HR VITON Streamlit?
You need Python installed on your system, along with the Streamlit library. A modern browser is also required for the best experience.

Can I use any type of clothing image with HR VITON Streamlit?
Yes, HR VITON supports various clothing formats, but ensure the images are high-quality and properly segmented for the best results.

How do I share my virtual try-on results?
You can download the generated image directly from the app or share the link to the Streamlit interface with others.

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