Project Name

LSD-VTON for Local Flow Global Parsing Warping integrated with Stable Diffusion Virtual Try-on

Developed and maintained By (Order Does not matter):

Mohamed Walid, Karim Metwally, Mohamed Mostafa, Mohamed Hesham, Omar Ehab, and Mohamed Ahmed

Introduction

The virtual tryon system is based on GP-VTON and LaDi-VTON

We exploit the GP-VTON power in warping(LFGP) and the LaDi-VTON power in generation(Stable diffusion)

Dataset: VITON-HD

Project Objective

• Create an e-commerce application that offers virtual try-on feature.
• Deal with challenging inputs:
  • Complex poses
  • Complex garments
  • Clothes style: tucked-in or tucked-out
• Train the developed warping and generative models.
• Evaluate the performance of the developed virtual try-on model against benchmarks.

LSD-VTON System Architecture

Used Technologies/Apps:

• Python
• FastAPI
• Kaggle API
• SQL Server
• HTML, CSS, JS
• Kaggle (P100 GPU 16 GB VRAM, 30 GB RAM)
• Pycharm IDE

Demo video

Click Here for the demo

Mody Test

In this section we will introduce our work (no code here) to test the GP-VTON, LaDi-VTON and LSD-VTON architectures but using new person/cloth images (which not included in the original dataset) i.e we will try-on our personal image and our clothes

I called it Mody Test!

For Mody Test (custom input) we only have (our inputs)

• Person image
• Cloth image

and in Mody Test we do a preprocessing task which includes complicated tasks which are:

• Person parse (Human parse)
• Person keypoints (skeleton)
• Person densepose
• Cloth parse
• Cloth binary mask

Here is a spoiler image for our work (Mody Test)

Citation

@inproceedings{xie2023gpvton,
  title     = {GP-VTON: Towards General Purpose Virtual Try-on via Collaborative Local-Flow Global-Parsing Learning},
  author    = {Zhenyu, Xie and Zaiyu, Huang and Xin, Dong and Fuwei, Zhao and Haoye, Dong and Xijin, Zhang and Feida, Zhu and Xiaodan, Liang},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  month     = {June},
  year      = {2023},
}

@inproceedings{morelli2023ladi,
  title={{LaDI-VTON: Latent Diffusion Textual-Inversion Enhanced Virtual Try-On}},
  author={Morelli, Davide and Baldrati, Alberto and Cartella, Giuseppe and Cornia, Marcella and Bertini, Marco and Cucchiara, Rita},
  booktitle={Proceedings of the ACM International Conference on Multimedia},
  year={2023}
}

Acknowledgments

Thanks for all authors of

• GP-VTON
• LaDi-VTON

License

The use of this code is RESTRICTED to non-commercial research and educational purposes.