65 lines
2.0 KiB
Markdown
65 lines
2.0 KiB
Markdown
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# Documentation
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- Class name: SaltMaskDominantRegion
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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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SaltMaskDominantRegion节点专注于根据指定阈值识别和分离一组给定蒙版中的主导区域。它可以有效地突出显示图像蒙版中最显著的区域，适用于需要聚焦重要蒙版区域的任务。
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# Input types
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## Required
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- masks
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- 需要进行主导区域检测的输入蒙版。这些蒙版对于确定图像中的感兴趣区域至关重要。
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- Comfy dtype: MASK
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- Python dtype: torch.Tensor
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- threshold
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- 用于区分蒙版中主导区域的阈值。它通过设置截止强度值，在定义何为"主导"区域方面起着关键作用。
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- Comfy dtype: INT
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- Python dtype: int
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# Output types
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- MASKS
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- 输出是一个突出显示主导区域的蒙版张量。这对于需要聚焦或操作蒙版主要区域的应用来说非常重要。
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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 SaltMaskDominantRegion:
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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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"threshold": ("INT", {"default":128, "min":0, "max":255, "step":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 = "dominant_region"
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def dominant_region(self, masks, threshold=128):
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if not isinstance(threshold, list):
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threshold = [threshold]
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regions = []
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for i, mask in enumerate(masks):
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mask_pil = mask2pil(mask.unsqueeze(0))
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region_mask = MaskFilters.dominant_region(mask_pil, int(threshold[i if i < len(threshold) 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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