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A newer version of the Gradio SDK is available: 5.7.1

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metadata
title: Change Cloth AI
emoji: 🔥
colorFrom: red
colorTo: pink
sdk: gradio
sdk_version: 5.4.0
app_file: app.py
pinned: false
license: mit

Change-cloth-AI🐨

A virtual try-on system that uses AI to visualize how different clothing items would look on a person.

Overview

Outfit Diffusion is an AI-powered virtual try-on system that allows users to:

  • Upload a photo of a person (model image)
  • Upload a photo of a clothing item
  • Generate realistic visualizations of how the clothing would look on the person

Features

  • Easy-to-use Interface: Simple upload system for both model and garment images
  • Pre-loaded Examples: Includes sample model and garment images for quick testing
  • Customizable Generation: Adjust parameters like:
    • Number of samples
    • Number of steps
    • Image scale
    • Random seed

How to Use

  1. Select or Upload Model Image

    • Choose from provided example models
    • Or upload your own model image (person wearing clothes)

  2. Select or Upload Garment

    • Choose from provided example garments
    • Or upload your own garment image

  3. Adjust Parameters (Optional)

    • Steps: Higher values give better quality but take longer
    • Scale: Affects how closely the output follows the input
    • Seed: Set for reproducible results

  4. Generate Output

    • Click "Generate Outfit" to create the visualization
    • Wait for processing (may take a few moments)

Technical Details

  • Built using Gradio interface
  • Powered by diffusion models
  • SDK Version: 5.4.0
  • Runs on Hugging Face Spaces

Limitations

  • Processing time depends on server load
  • Free tier has usage quotas
  • Best results with clear, front-facing photos
  • Garment images should be on white/clear backgrounds

Tips for Best Results

  1. Use clear, well-lit photographs
  2. Model should be in a natural, front-facing pose
  3. Garment images should be isolated on clean backgrounds
  4. Start with lower step counts (10-15) for quick tests
  5. Increase steps for final, higher-quality results

Error Handling

If you encounter quota errors:

  • Wait a few minutes between attempts
  • Try reducing the number of steps
  • Consider signing up for a Hugging Face account for more quota

Author

Ali Hamza Kamboh (AHKamBoh)

Credits

This project uses the Hugging Face Spaces infrastructure and is built on top of state-of-the-art diffusion models for virtual try-on applications.

License

MIT License

Copyright (c) 2024 Ali Hamza Kamboh (AHKamBoh)

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information about the configuration, visit: https://huggingface.co/docs/hub/spaces-config-reference