65 lines
2.0 KiB
Markdown
65 lines
2.0 KiB
Markdown
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# Documentation
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- Class name: SaltMaskSmoothRegion
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- Category: SALT/Masking/Filter
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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SaltMaskSmoothRegion节点用于对遮罩区域应用平滑滤镜，通过指定的sigma值来控制平滑程度。这一处理过程通过减少噪点和不规则性来提升遮罩区域的视觉质量。
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# Input types
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## Required
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- masks
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- masks参数代表需要进行平滑处理的输入遮罩，是节点处理的主要数据。
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- Comfy dtype: MASK
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- Python dtype: torch.Tensor
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- sigma
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- sigma参数控制应用于遮罩区域的平滑滤镜的平滑程度，直接影响平滑效果和噪点减少的程度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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# Output types
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- MASKS
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- 输出是根据指定sigma值进行平滑处理后的遮罩张量，通过减少噪点和不规则性来提供更高的视觉质量。
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- Comfy dtype: MASK
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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: unknown
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## Source code
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```python
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class SaltMaskSmoothRegion:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"masks": ("MASK",),
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"sigma": ("FLOAT", {"default":5.0, "min":0.0, "max":128.0, "step":0.1}),
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}
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}
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CATEGORY = f"{NAME}/Masking/Filter"
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RETURN_TYPES = ("MASK",)
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RETURN_NAMES = ("MASKS",)
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FUNCTION = "smooth_region"
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def smooth_region(self, masks, sigma=128):
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if not isinstance(sigma, list):
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sigma = [sigma]
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regions = []
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for i, mask in enumerate(masks):
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pil_image = mask2pil(mask.unsqueeze(0))
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region_mask = MaskFilters.smooth_region(pil_image, sigma[i if i < len(sigma) else -1])
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region_tensor = pil2mask(region_mask)
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regions.append(region_tensor)
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regions_tensor = torch.cat(regions, dim=0)
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return (regions_tensor,)
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```
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