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+ ---
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+ language:
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+ - en
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+ pipeline_tag: unconditional-image-generation
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+ tags:
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+ - Diffusion Models
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+ - Stable Diffusion
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+ - Perturbed-Attention Guidance
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+ - PAG
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+ ---
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+
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+ # Perturbed-Attention Guidance
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+
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+ [Project](https://ku-cvlab.github.io/Perturbed-Attention-Guidance/) / [arXiv](https://arxiv.org/abs/2403.17377) / [GitHub](https://github.com/KU-CVLAB/Perturbed-Attention-Guidance)
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+
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+ This repository is based on [Diffusers](https://huggingface.co/docs/diffusers/index). The pipeline is a modification of StableDiffusionPipeline to support inpainting with Perturbed-Attention Guidance (PAG).
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+
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+ ## Quickstart
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+
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+ Loading Custom Piepline:
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+
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+ ```
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+ from diffusers import StableDiffusionPipeline
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+
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+ pipe = StableDiffusionPipeline.from_pretrained(
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+ "runwayml/stable-diffusion-inpainting",
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+ custom_pipeline="hyoungwoncho/sd_perturbed_attention_guidance_inpaint",
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+ torch_dtype=torch.float16,
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+ safety_checker=None
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+ )
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+
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+ device="cuda"
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+ pipe = pipe.to(device)
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+ ```
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+
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+ Inpainting with PAG:
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+
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+ ```
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+ output = pipe(
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+ prompts,
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+ image=init_image,
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+ mask_image=mask_image,
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+ num_inference_steps=50,
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+ guidance_scale=0.0,
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+ pag_scale=5.0,
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+ pag_applied_layers_index=['m0']
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+ ).images[0]
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+ ```
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+
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+ ## Parameters
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+
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+ guidance_scale : gudiance scale of CFG (ex: 7.5)
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+
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+ pag_scale : gudiance scale of PAG (ex: 5.0)
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+
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+ pag_applied_layers_index : index of the layer to apply perturbation (ex: ['m0'])