65 lines
2.1 KiB
Markdown
65 lines
2.1 KiB
Markdown
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# Documentation
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- Class name: SaltMaskDilateRegion
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- Category: SALT/Masking/Filter
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- Output node: False
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- Repo Ref: https://github.com/saltai-mlops/ComfyUI/blob/main/custom_nodes/salt_filters/salt_filters.py
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SaltMaskDilateRegion节点在掩码区域应用膨胀滤波器，根据指定的迭代次数有效扩大掩码中的感兴趣区域。该节点旨在处理和修改掩码区域，以突出或放大掩码内的特定特征。
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# Input types
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## Required
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- masks
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- 输入需要进行膨胀处理的掩码。这个参数对于定义图像中将要进行膨胀的区域至关重要，直接影响节点的输出结果。
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- Comfy dtype: MASK
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- Python dtype: torch.Tensor
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- iterations
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- 指定对掩码应用膨胀操作的次数。这个参数控制膨胀的程度，影响掩码内特征的大小和可见性。
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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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- 经过膨胀处理后的输出掩码。这些掩码呈现了经过修改的区域，其中感兴趣的区域已被扩大，展示了膨胀过程的效果。
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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 SaltMaskDilateRegion:
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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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"iterations": ("INT", {"default":5, "min":1, "max":64, "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 = "dilate_region"
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def dilate_region(self, masks, iterations=5):
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if not isinstance(iterations, list):
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iterations = [iterations]
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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.dilate_region(pil_image, iterations[i if i < len(iterations) 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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