96 lines
3.6 KiB
Markdown
96 lines
3.6 KiB
Markdown
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# Documentation
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- Class name: ConditioningSetMaskAndCombine
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- Category: KJNodes/masking/conditioning
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- Output node: False
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该节点旨在对条件数据应用蒙版，根据指定的蒙版及其强度调整条件。它结合了设置蒙版和合并条件数据的功能，允许动态改变给定数据集中的条件区域。
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# Input types
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## Required
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- positive_i
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- 指定一组受相应蒙版正面影响的条件数据，在将条件定制到数据的特定区域或方面中起关键作用。
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- Comfy dtype: CONDITIONING
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- Python dtype: torch.Tensor
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- negative_i
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- 指定一组受相应蒙版负面影响的条件数据，对于从条件中排除或减弱某些区域或方面至关重要。
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- Comfy dtype: CONDITIONING
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- Python dtype: torch.Tensor
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- mask_i
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- 应用于相应条件数据的蒙版，决定正面或负面条件调整的影响区域。
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- Comfy dtype: MASK
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- Python dtype: torch.Tensor
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- mask_i_strength
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- 定义蒙版对条件的影响强度，允许对蒙版如何显著影响条件进行精细控制。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- set_cond_area
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- 决定是将条件区域设置为蒙版的边界还是使用默认设置，影响条件调整的范围和精度。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: bool
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# Output types
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- combined_positive
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- 蒙版应用后所有正面条件数据的组合结果，反映了正面调整的累积效果。
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- Comfy dtype: CONDITIONING
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- Python dtype: torch.Tensor
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- combined_negative
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- 蒙版应用后所有负面条件数据的组合结果，反映了负面调整的累积效果。
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- Comfy dtype: CONDITIONING
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- Python dtype: torch.Tensor
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class ConditioningSetMaskAndCombine:
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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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"positive_1": ("CONDITIONING", ),
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"negative_1": ("CONDITIONING", ),
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"positive_2": ("CONDITIONING", ),
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"negative_2": ("CONDITIONING", ),
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"mask_1": ("MASK", ),
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"mask_2": ("MASK", ),
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"mask_1_strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
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"mask_2_strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
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"set_cond_area": (["default", "mask bounds"],),
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}
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}
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RETURN_TYPES = ("CONDITIONING","CONDITIONING",)
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RETURN_NAMES = ("combined_positive", "combined_negative",)
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FUNCTION = "append"
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CATEGORY = "KJNodes/masking/conditioning"
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DESCRIPTION = """
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Bundles multiple conditioning mask and combine nodes into one,functionality is identical to ComfyUI native nodes
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"""
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def append(self, positive_1, negative_1, positive_2, negative_2, mask_1, mask_2, set_cond_area, mask_1_strength, mask_2_strength):
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c = []
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c2 = []
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set_area_to_bounds = False
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if set_cond_area != "default":
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set_area_to_bounds = True
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if len(mask_1.shape) < 3:
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mask_1 = mask_1.unsqueeze(0)
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if len(mask_2.shape) < 3:
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mask_2 = mask_2.unsqueeze(0)
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for t in positive_1:
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append_helper(t, mask_1, c, set_area_to_bounds, mask_1_strength)
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for t in positive_2:
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append_helper(t, mask_2, c, set_area_to_bounds, mask_2_strength)
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for t in negative_1:
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append_helper(t, mask_1, c2, set_area_to_bounds, mask_1_strength)
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for t in negative_2:
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append_helper(t, mask_2, c2, set_area_to_bounds, mask_2_strength)
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return (c, c2)
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```
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