75 lines
2.2 KiB
Markdown
75 lines
2.2 KiB
Markdown
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# Documentation
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- Class name: RemapMaskRange
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- Category: KJNodes/masking
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- Output node: False
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RemapMaskRange 节点的设计目的是调整掩码中的值范围至新指定的最小值和最大值，确保掩码的值适当地缩放到这个新范围内。
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# Input types
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## Required
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- mask
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- 需要重新映射值的掩码。这个输入对于定义将要进行范围调整的源数据至关重要。
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- Comfy dtype: MASK
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- Python dtype: torch.Tensor
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- min
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- 指定重新映射范围中的新最小值。这个参数设置掩码值的目标范围的下限。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- max
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- 定义重新映射范围中的新最大值。这个参数确立掩码值的目标范围的上限。
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- Comfy dtype: FLOAT
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- Python dtype: float
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# Output types
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- mask
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- 输出是值已重新映射到新指定范围的掩码，确保所有值都落在这个定义的区间内。
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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 RemapMaskRange:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"mask": ("MASK",),
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"min": ("FLOAT", {"default": 0.0,"min": -10.0, "max": 1.0, "step": 0.01}),
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"max": ("FLOAT", {"default": 1.0,"min": 0.0, "max": 10.0, "step": 0.01}),
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}
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}
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RETURN_TYPES = ("MASK",)
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RETURN_NAMES = ("mask",)
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FUNCTION = "remap"
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CATEGORY = "KJNodes/masking"
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DESCRIPTION = """
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Sets new min and max values for the mask.
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"""
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def remap(self, mask, min, max):
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# Find the maximum value in the mask
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mask_max = torch.max(mask)
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# If the maximum mask value is zero, avoid division by zero by setting it to 1
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mask_max = mask_max if mask_max > 0 else 1
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# Scale the mask values to the new range defined by min and max
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# The highest pixel value in the mask will be scaled to max
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scaled_mask = (mask / mask_max) * (max - min) + min
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# Clamp the values to ensure they are within [0.0, 1.0]
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scaled_mask = torch.clamp(scaled_mask, min=0.0, max=1.0)
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return (scaled_mask, )
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```
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