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Text-based Vector Sketch Editing with Image Editing Diffusion Prior (ICME 2024)

[Paper]

This code is used for editing vector sketches with text prompts.

Outline

Installation

  1. Please follow instructions in ximinng/DiffSketcher for the step-by-step environment preparation.
  2. Download the CompVis/stable-diffusion-v1-4 models and place them somewhere. Follow file structure here.
  3. Finally, modify the directory path of your downloaded models to huggingface_model_dict["sd14"](Line 11) of ./methods/diffusers_warp/__init__.py.

Quick Start

Use the code run_painterly_render.py and scroll to Line 81. Then, modify the code according to the following instructions:

  1. Set one or more seeds, or choose random ones.
  2. Choose the editing type. replace, refine and reweight stand for editing modes Word Swap, Prompt Refinement and Attention Re-weighting, respectively.
  3. Set the prompt information.

Examples

(a) Word Swap (replace)

seeds_list = [25760]
args.edit_type = "replace"

PromptInfo(prompts=["A painting of a squirrel eating a burger",
                    "A painting of a rabbit eating a burger",
                    "A painting of a rabbit eating a pumpkin",
                    "A painting of a owl eating a pumpkin"],
           token_ind=5,
           changing_region_words=[["", ""], ["squirrel", "rabbit"], ["burger", "pumpkin"], ["rabbit", "owl"]])
  • token_ind: indicate the index of cross-attn maps for initializing strokes.
  • changing_region_words: for local editing. Type in two words to indicate the changing regions during each edit. Use empty strings for the first edit.
Original image and sketch Edited image and sketch 1 Edited image and sketch 2 Edited image and sketch 3

(b) Prompt Refinement (refine)

seeds_list = [53487]
args.edit_type = "refine"

PromptInfo(prompts=["An evening dress",
                    "An evening dress with sleeves",
                    "An evening dress with sleeves and a belt"],
           token_ind=3,
           changing_region_words=[["", ""], ["", "sleeves"], ["", "belt"]]),
  • changing_region_words: set an empty string for the first words.
Original image and sketch Edited image and sketch 1 Edited image and sketch 2

(c) Attention Re-weighting (reweight)

seeds_list = [35491]
args.edit_type = "reweight"

PromptInfo(prompts=["An emoji face with moustache and smile"] * 3,
           token_ind=3,
           changing_region_words=[["", ""], ["moustache", "moustache"], ["smile", "smile"]],
           reweight_word=["moustache", "smile"],
           reweight_weight=[-1.0, 3.0]),
  • changing_region_words: set the same words for each pair.
  • reweight_word / reweight_weight: word or weight for reweighting at each edit.
Original image and sketch Edited image and sketch 1 Edited image and sketch 2

Acknowledgement

The project is built upon ximinng/DiffSketcher and google/prompt-to-prompt. We thank all the authors for their effort.

Citation

If you use the code please cite:

@inproceedings{mo2024text,
  title={Text-based Vector Sketch Editing with Image Editing Diffusion Prior},
  author={Mo, Haoran and Lin, Xusheng and Gao, Chengying and Wang, Ruomei},
  booktitle={2024 IEEE International Conference on Multimedia and Expo (ICME)},
  pages={1--6},
  year={2024},
  organization={IEEE}
}