metadata

title: ClothQuill - AI Clothing Inpainting
emoji: 👕
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.25.1
app_file: app.py
pinned: false

ClothQuill - AI Clothing Inpainting

🎨 An AI-powered tool for seamlessly editing and modifying clothing in images using state-of-the-art deep learning models.

Demo • Features • Installation • Usage • Examples • Technical Details

Demo

ClothQuill is available as a Hugging Face Space! Try it out here: ClothQuill Demo

Features

🎯 Precise Clothing Detection: Automatically identifies and segments different clothing items
🎨 Interactive Selection: Choose specific clothing parts to modify
🔄 Multiple Variations: Generate multiple inpainting results for each prompt
🎛️ Adjustable Controls: Fine-tune mask dilation for better blending
🖼️ High-Quality Output: Maintains image quality with advanced upscaling
🚀 Real-time Preview: See segmentation masks and selected regions in real-time

Installation

# Clone the repository
git clone https://huggingface.co/spaces/bismay/ClothQuill
cd ClothQuill

# Install dependencies
pip install -r requirements.txt

# Download required models (will be downloaded automatically on first run)
python download_models.py

Usage

Start the Application
```
python app.py
```
Using the Interface
- Upload an image containing a person
- The app will automatically detect clothing regions
- Select which parts of the clothing you want to modify
- Adjust the mask dilation if needed
- Enter a prompt describing the desired clothing
- Click "Generate" to create multiple variations
Advanced Options
- Use the dilation slider to control the modification area
- Select multiple clothing parts for simultaneous editing
- Preview the segmentation mask before generating

Examples

Here are some example prompts and their use cases:

🧥 Outerwear: "A stylish black leather jacket with silver zippers"
👔 Formal: "A navy blue pinstripe suit with a white dress shirt"
👕 Casual: "A comfortable gray hoodie with white drawstrings"
👗 Dresses: "A flowing red summer dress with floral patterns"
👖 Pants: "Dark blue distressed jeans with a vintage wash"

Technical Details

ClothQuill combines multiple state-of-the-art models:

Segmentation: SegFormer for precise clothing detection
Inpainting: Stable Diffusion 2.0 for high-quality image generation
Upscaling: RealESRGAN for maintaining image quality

Model Architecture

Input Image → SegFormer (Segmentation) → User Selection → 
Mask Generation → Stable Diffusion (Inpainting) → 
RealESRGAN (Upscaling) → Final Output

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

Thanks to the Hugging Face team for hosting the demo
Stable Diffusion by Stability AI
SegFormer implementation by mattmdjaga
RealESRGAN by xinntao