Project | Arxiv | Demo | ComfyUI | Data
[ICCV 2025 Best Student Paper] Official Pytorch implementation of the paper: "FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models"
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Clone the repository
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Install the required dependencies using
pip install torch diffusers transformers accelerate sentencepiece protobuf- New version of diffusers may have compatibility issues, try install
diffusers==0.30.1 - Tested with CUDA version 12.4 and diffusers 0.30.0
- New version of diffusers may have compatibility issues, try install
Run editing with Stable Diffusion 3: python run_script.py --exp_yaml SD3_exp.yaml
Run editing with Flux: python run_script.py --exp_yaml FLUX_exp.yaml
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Upload images to
example_imagesfolder. -
Create an edits file that specifies: (a) a path to the input image, (b) a source prompt, (c) target prompts, and (d) target codes. The target codes summarize the changes between the source and target prompts and will appear in the output filename.
Seeedits.yamlfor example. -
Create an experiment file containing the hyperparamaters needed for running FlowEdit, such as
n_max,n_min. This file also includes the path to theedits.yamlfile
SeeFLUX_exp.yamlfor FLUX usage example andSD3_exp.yamlfor Stable Diffusion 3 usage example.
For a detailed discussion on the impact of different hyperparameters and the values we used, please refer to our paper.
Run python run_script.py --exp_yaml <path to your experiment yaml>
Implemented by logtd
LTX-Video ComfyUI implementation can be found in LTX-Video official repository.
This project is licensed under the MIT License.
If you use this code for your research, please cite our paper:
@article{kulikov2024flowedit,
title = {FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models},
author = {Kulikov, Vladimir and Kleiner, Matan and Huberman-Spiegelglas, Inbar and Michaeli, Tomer},
journal = {arXiv preprint arXiv:2412.08629},
year = {2024}
}
