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'%3e%3cpath d='M22.941142499999998%2c18.4907265625C20.7973025%2c21.2337465625%2c18.653602499999998%2c23.9764965625%2c16.5096155%2c26.719196562500002C15.7464715%2c27.6958965625%2c16.4596735%2c29.1035265625%2c17.7179125%2c29.1035265625L30.5804125%2c29.1035265625C31.8385125%2c29.1035265625%2c32.5519125%2c27.6958965625%2c31.7883125%2c26.719196562500002C29.6448125%2c23.9764965625%2c27.500812500000002%2c21.2337965625%2c25.3570725%2c18.4907265625C24.7489725%2c17.7127265625%2c23.5494225%2c17.7127265625%2c22.941142499999998%2c18.4907265625ZM24.0441925%2c19.3528665625L24.0440425%2c19.3530465625L19.6246325%2c25.0074065625L17.6126225%2c27.5813865625Q17.5882425%2c27.6125865625%2c17.6045625%2c27.6447765625Q17.6343025%2c27.7034865625%2c17.7179125%2c27.7034865625L30.5804125%2c27.7034865625Q30.663912500000002%2c27.7034865625%2c30.6937125%2c27.6448265625Q30.7099125%2c27.6128265625%2c30.685412499999998%2c27.5814965625L24.254022499999998%2c19.3528565625Q24.2183525%2c19.3072265625%2c24.149182500000002%2c19.3072265625Q24.0800125%2c19.3072265625%2c24.0441925%2c19.3528665625Z' fill-rule='evenodd' fill='%23BEC4CA' fill-opacity='1'/%3e%3c/g%3e%3c/g%3e%3c/svg%3e)
工作流名称：东方树叶商品图摄影
【工作流介绍】
这个工作流程极为方便、简洁且高效。首先，您需要上传一张产品底图，我们以东方树叶饮料为例，不过您当然也可以选择其他产品的底图。接着，请上传一张与您的产品相关的背景参考图。通过 G-DinoSAM 语义分割进行语义分割，再利用 IPAdapter 进行风格迁移，同时借助 controlnet 控制产品形体。一旦完成上传操作，只需轻轻点击运行按钮，便能够快速生成处理结果。这个工作流程能够确保为您提供出色的效果。快来尝试一下吧！让我们为您呈现出令人赞叹不已的图像处理结果！
【使用场景】
如果您是一家饮料公司的设计师，想要为新推出的饮品制作广告图片，就可以利用这个工作流程。上传饮品的底图和一个富有创意的背景参考图，经过处理后，得到一张极具吸引力的广告图像，能够更好地展示产品的特点和魅力。
【关键节点】
G-DinoSAM语义分割，IPAdapter,controlnet
【模型版本】
SD1.5
模型名称:epicrealism_naturalSinRC1VAE.safetensors
【LoRA模型】
无
【ControlNet应用】
无
【K采样器】
CFG：5.9
采样方法：euler ancestral
调度器：normal
降噪：0.9
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工作流名称：东方树叶商品图摄影
【工作流介绍】
这个工作流程极为方便、简洁且高效。首先，您需要上传一张产品底图，我们以东方树叶饮料为例，不过您当然也可以选择其他产品的底图。接着，请上传一张与您的产品相关的背景参考图。通过 G-DinoSAM 语义分割进行语义分割，再利用 IPAdapter 进行风格迁移，同时借助 controlnet 控制产品形体。一旦完成上传操作，只需轻轻点击运行按钮，便能够快速生成处理结果。这个工作流程能够确保为您提供出色的效果。快来尝试一下吧！让我们为您呈现出令人赞叹不已的图像处理结果！
【使用场景】
如果您是一家饮料公司的设计师，想要为新推出的饮品制作广告图片，就可以利用这个工作流程。上传饮品的底图和一个富有创意的背景参考图，经过处理后，得到一张极具吸引力的广告图像，能够更好地展示产品的特点和魅力。
【关键节点】
G-DinoSAM语义分割，IPAdapter,controlnet
【模型版本】
SD1.5
模型名称:epicrealism_naturalSinRC1VAE.safetensors
【LoRA模型】
无
【ControlNet应用】
无
【K采样器】
CFG：5.9
采样方法：euler ancestral
调度器：normal
降噪：0.9
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Primitive Nodes (11) Custom Nodes (26)