82 lines
3.5 KiB
Markdown
82 lines
3.5 KiB
Markdown
# Set Props and Combine Cond 🎭🅐🅓
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## Documentation
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- Class name: ADE_ConditioningSetMaskAndCombine
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- Category: Animate Diff 🎭🅐🅓/conditioning/single cond ops
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- Output node: False
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- Repo Ref: https://github.com/Kosinkadink/ComfyUI-AnimateDiff-Evolved.git
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此节点专门用于生成模型的高级条件数据操作，特别关注掩码和附加条件层的应用和组合。它通过应用掩码、强度调整和整合新的条件数据来增强或修改现有条件，从而允许对生成过程进行更精确的控制。
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## Input types
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### Required
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- cond
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- 要增强或修改的原始条件数据。它作为应用附加条件层和掩码的基础，直接影响最终输出。
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- Comfy dtype: CONDITIONING
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- Python dtype: CustomType[CONDITIONING]
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- cond_ADD
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- 要与原始条件结合的附加条件数据。此层应用于现有条件之上，允许引入新特性或修改。
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- Comfy dtype: CONDITIONING
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- Python dtype: CustomType[CONDITIONING]
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- strength
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- 一个标量值，确定掩码应用于条件的强度。它控制附加条件和掩码对原始数据的影响程度。
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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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- 指定在条件数据中进行修改的区域，而不提及特定类型。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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### Optional
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- opt_mask
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- 一个可选掩码，可以应用于条件数据。它允许选择性地增强或修改条件中的特定区域。
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- Comfy dtype: MASK
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- Python dtype: torch.Tensor
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- opt_lora_hook
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- 一个可选的LoraHookGroup，可以应用于进一步操作条件数据。它提供了修改条件的额外灵活性。
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- Comfy dtype: LORA_HOOK
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- Python dtype: LoraHookGroup
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- opt_timesteps
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- 用于条件操作的可选时间步。此参数允许在生成过程中的特定点应用修改。
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- Comfy dtype: TIMESTEPS_COND
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- Python dtype: TimestepsCond
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## Output types
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- conditioning
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- Comfy dtype: CONDITIONING
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- 应用附加条件层、掩码和调整后的增强或修改的条件数据。
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- Python dtype: CustomType[CONDITIONING]
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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 ConditioningSetMaskAndCombineHooked:
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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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"cond": ("CONDITIONING",),
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"cond_ADD": ("CONDITIONING",),
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"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
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"set_cond_area": (COND_CONST._LIST_COND_AREA,),
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},
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"optional": {
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"opt_mask": ("MASK", ),
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"opt_lora_hook": ("LORA_HOOK",),
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"opt_timesteps": ("TIMESTEPS_COND",)
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}
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}
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RETURN_TYPES = ("CONDITIONING",)
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CATEGORY = "Animate Diff 🎭🅐🅓/conditioning/single cond ops"
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FUNCTION = "append_and_combine"
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def append_and_combine(self, conditioning, conditioning_ADD,
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strength: float, set_cond_area: str,
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opt_mask: Tensor=None, opt_lora_hook: LoraHookGroup=None, opt_timesteps: TimestepsCond=None):
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(final_conditioning,) = set_mask_and_combine_conds(conds=[conditioning], new_conds=[conditioning_ADD],
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strength=strength, set_cond_area=set_cond_area,
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opt_mask=opt_mask, opt_lora_hook=opt_lora_hook, opt_timesteps=opt_timesteps)
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return (final_conditioning,) |