Image-to-Image
Diffusers
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Update README.md

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  ---
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- license: gpl-3.0
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  pipeline_tag: image-to-image
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  library_name: diffusers
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  base_model:
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  > Recent interactive matting methods have shown satisfactory performance in capturing the primary regions of objects, but they fall short in extracting fine-grained details in edge regions. Diffusion models trained on billions of image-text pairs demonstrate exceptional capability in modeling highly complex data distributions and synthesizing realistic texture details, while exhibiting robust text-driven interaction capabilities — making them an attractive solution for interactive matting.
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+ license: openrail++
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  pipeline_tag: image-to-image
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  library_name: diffusers
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  base_model:
 
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  > Recent interactive matting methods have shown satisfactory performance in capturing the primary regions of objects, but they fall short in extracting fine-grained details in edge regions. Diffusion models trained on billions of image-text pairs demonstrate exceptional capability in modeling highly complex data distributions and synthesizing realistic texture details, while exhibiting robust text-driven interaction capabilities — making them an attractive solution for interactive matting.
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