try Off Anyone

Introduction

"TryOffAnyone" is a model designed for generating tiled cloth patterns from images of dressed individuals. The model utilizes advanced image diffusion techniques to facilitate virtual try-off applications in the fashion and e-commerce sectors.

Architecture

The model is based on the stable-diffusion-v1-5 framework, specifically using the stable-diffusion-inpainting base model. It operates within the image-to-image pipeline and leverages the Diffusers library for processing. The architecture supports tasks such as virtual try-on and try-off, making it suitable for applications in fashion and e-commerce.

Training

The model was developed as part of the research detailed in the paper "TryOffAnyone: Tiled Cloth Generation from a Dressed Person." The training process involved the use of diffusion techniques to enable the transformation of images to generate realistic cloth patterns.

Guide: Running Locally

1. Setup Environment: Ensure you have Python installed. Set up a virtual environment and install the required packages, including the Diffusers library.
2. Clone Repository: Clone the GitHub repository here.
3. Download Model: Access the model files from the Hugging Face hub and place them in the appropriate directory.
4. Run Model: Execute the script provided in the repository to start generating cloth patterns from input images.

For optimal performance, consider using cloud-based GPUs from providers like AWS, Google Cloud, or Azure to handle intensive computations involved in image processing.

License

The TryOffAnyone model is licensed under the Server Side Public License. For more details, visit the license page.