54 lines
1.8 KiB
Markdown
54 lines
1.8 KiB
Markdown
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# Documentation
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- Class name: InpaintPreprocessor
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- Category: ControlNet Preprocessors/others
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- Output node: False
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InpaintPreprocessor节点旨在通过将掩码应用于输入图像来为修复任务准备图像。它通过标记掩码指定的区域（这些区域需要修复）来修改图像，从而有效地为进一步处理做准备，使这些区域可以被填充或修正。
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# Input types
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## Required
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- image
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- image参数代表需要修复的输入图像。它对于定义在修复过程中保持不变的区域至关重要。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- mask
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- mask参数指定了图像中需要修复的区域。它在识别应由修复算法处理或填充的图像部分方面起着关键作用。
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- Comfy dtype: MASK
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- Python dtype: torch.Tensor
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# Output types
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- image
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- 输出是输入图像的修改版本，其中由掩码指定的区域被标记为需要修复，为进一步处理做好准备。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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## Usage tips
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- Infra type: `GPU`
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- Common nodes:
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- [ControlNetApplyAdvanced](../../Comfy/Nodes/ControlNetApplyAdvanced.md)
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- [ImageScale](../../Comfy/Nodes/ImageScale.md)
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## Source code
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```python
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class InpaintPreprocessor:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "image": ("IMAGE",), "mask": ("MASK",)}}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "preprocess"
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CATEGORY = "ControlNet Preprocessors/others"
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def preprocess(self, image, mask):
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mask = torch.nn.functional.interpolate(mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])), size=(image.shape[1], image.shape[2]), mode="bilinear")
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mask = mask.movedim(1,-1).expand((-1,-1,-1,3))
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image = image.clone()
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image[mask > 0.5] = -1.0 # set as masked pixel
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return (image,)
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```
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