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Enhancing the Diversity in Image Synthesis with a Reference-Based Stochastic Diffusion Inversion (sEDICT)

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sEDICT (stochastic EDICT)

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The baseline model is EDICT: Exact Diffusion Inversion via Coupled Transformation in this repository.

Experimental Results

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Run Example

# reference-based image generation
python -u s_EDICT.py --b_prompt 'A dog' --t_prompt 'A dog' --s_i 0.7 --s_d 0.8 --seed 1 --scale 0.2

# image editing
python -u s_EDICT.py --b_prompt 'A dog' --t_prompt 'A golden retriever' --s_i 0.7 --s_d 0.8 --seed 1 --scale 0.2

Evaluation

python -u qualitative_evaluation.py --reference_img_path REF_PATH --generated_img_path GEN_PATH

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Enhancing the Diversity in Image Synthesis with a Reference-Based Stochastic Diffusion Inversion (sEDICT)

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