Haofeng Liu    Chenshu Xu    Yifei Yang    Lihua Zeng    Shengfeng He

     DragNoise       DragDiffusion       DragNoise       DragDiffusion

     DragNoise       DragDiffusion       DragNoise       DragDiffusion

     DragNoise       DragDiffusion       DragNoise       DragDiffusion

     DragNoise       DragNoise        DragNoise       DragNoise

• [Apr 5th] v1.0.0 Release.

It is recommended to run our code on a Nvidia GPU with a linux system. Currently, it requires around 14 GB GPU memory to run our method.

To install the required libraries, simply run the following command:

conda env create -f environment.yaml
conda activate dragnoise

To start with, in command line, run the following to start the gradio user interface:

python3 drag_ui.py

Basically, it consists of the following steps:

• Drop our input image into the left-most box.
• Input a prompt describing the image in the "prompt" field
• Click the "Train LoRA" button to train a LoRA given the input image

• Draw a mask in the left-most box to specify the editable areas. (optional)
• Click handle and target points in the middle box. Also, you may reset all points by clicking "Undo point".
• Click the "Run" button to run our algorithm. Edited results will be displayed in the right-most box.

Code related to the Drag algorithm is under Apache 2.0 license.

If you find our repo helpful, please consider leaving a star or cite our paper :

@misc{liu2024drag,
      title={Drag Your Noise: Interactive Point-based Editing via Diffusion Semantic Propagation}, 
      author={Haofeng Liu and Chenshu Xu and Yifei Yang and Lihua Zeng and Shengfeng He},
      year={2024},
      eprint={2404.01050},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

For any questions on this project, please contact [email protected]

This work is inspired by the amazing DragGAN. We also benefit from the codebase of DragDiffusion.

• Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
• DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing
• DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models
• FreeDrag: Point Tracking is Not You Need for Interactive Point-based Image Editing

1. For users struggling in loading models from huggingface due to internet constraint, please 1) follow this links and download the model into the directory "local_pretrained_models"; 2) Run "drag_ui.py" and select the directory to your pretrained model in "Algorithm Parameters -> Base Model Config -> Diffusion Model Path".