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Cog implementation of FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models

Zero-Shot Image Editing Python PyTorch

How to use

Make sure you have cog installed.

To run a prediction:

cog predict -i image="./image.png" -i model_type="FLUX" -i source_prompt="a cat sitting in the grass"  -i target_prompt="a puppy sitting in the grass"

Recommend settings

FLUX

  • Steps = 28
  • Guidance (CFG) = 1.5
  • TAR guidance = 5.5 – n_max = 24

SD3

  • Steps = 50
  • Guidance (CFG) = 3.5
  • TAR guidance = 13.5 – n_max = 33

Credits: FlowEdit

Project | Arxiv | Demo | ComfyUI

Official Pytorch implementation of the paper: "FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models"

License

The code in this repository is licensed under the Apache-2.0 License.

Flux Dev falls under the FLUX.1 [dev] Non-Commercial License.

FLUX.1 [dev] fine-tuned weights and their outputs are non-commercial by default, but can be used commercially when running on Replicate.

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Cog implementation of FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models

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