README.md

metadata

title: StableVITON Virtual Try-On
emoji: 👕
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
license: mit
app_port: 7860
version: 1.0.1

StableVITON Virtual Try-On Backend

AI-powered virtual try-on service using StableVITON and FastAPI.

Features

• Virtual try-on inference via REST API
• Support for JPEG/PNG images
• Automatic image preprocessing and validation
• GPU-optimized inference (CUDA support)
• Single-request processing to prevent OOM
• Comprehensive error handling

API Documentation

POST /tryon

Perform virtual try-on inference.

Request:

• person_image: Full-body photo (multipart/form-data)
• garment_image: Garment image (multipart/form-data)

Response:

{
  "success": true,
  "result_image": "data:image/png;base64,...",
  "processing_time": 23.4,
  "model_version": "stablevton-v1"
}

GET /health

Health check endpoint.

Local Development

# Install dependencies
pip install -r requirements.txt

# Run server
python main.py

Deployment

This project is designed to run on Hugging Face Spaces with Docker SDK.

1. Create a Space with Docker SDK
2. Select GPU hardware (T4 small is sufficient)
3. Push the code to the Space