Set Props on Cond 🎭🅐🅓¶
Documentation¶
- Class name:
ADE_ConditioningSetMask
- Category:
Animate Diff 🎭🅐🅓/conditioning/single cond ops
- Output node:
False
This node is designed to apply a mask to conditioning data, adjusting the area and strength of the conditioning based on specified parameters. It enables the dynamic modification of conditioning inputs to better align with desired outcomes, such as focusing on or excluding specific areas within the data.
Input types¶
Required¶
cond_ADD
- The conditioning data to be added or modified. This parameter is essential for introducing new contexts or content into the existing conditioning framework.
- Comfy dtype:
CONDITIONING
- Python dtype:
Tensor
strength
- Defines the intensity of the mask's effect on the conditioning data, allowing for fine-tuned control over the modification's impact.
- Comfy dtype:
FLOAT
- Python dtype:
float
set_cond_area
- Determines whether the mask's effect is applied to the default area or the bounds of the mask, providing flexibility in targeting specific regions.
- Comfy dtype:
COMBO[STRING]
- Python dtype:
str
Optional¶
opt_mask
- An optional mask that specifies the areas of the conditioning data to be modified, offering additional control over which parts of the conditioning are affected.
- Comfy dtype:
MASK
- Python dtype:
Tensor
opt_lora_hook
- An optional parameter that allows for the application of Lora hooks to the conditioning, further customizing the conditioning process.
- Comfy dtype:
LORA_HOOK
- Python dtype:
LoraHookGroup
opt_timesteps
- Optional timesteps conditioning, enabling temporal adjustments to the conditioning data.
- Comfy dtype:
TIMESTEPS_COND
- Python dtype:
TimestepsCond
Output types¶
conditioning
- Comfy dtype:
CONDITIONING
- The modified conditioning data, reflecting the applied mask and adjustments, including any additional conditioning data added.
- Python dtype:
Tensor
- Comfy dtype:
Usage tips¶
- Infra type:
CPU
- Common nodes: unknown
Source code¶
class ConditioningSetMaskHooked:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"cond_ADD": ("CONDITIONING",),
"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}),
"set_cond_area": (COND_CONST._LIST_COND_AREA,),
},
"optional": {
"opt_mask": ("MASK", ),
"opt_lora_hook": ("LORA_HOOK",),
"opt_timesteps": ("TIMESTEPS_COND",)
}
}
RETURN_TYPES = ("CONDITIONING",)
CATEGORY = "Animate Diff 🎭🅐🅓/conditioning/single cond ops"
FUNCTION = "append_and_hook"
def append_and_hook(self, cond_ADD,
strength: float, set_cond_area: str,
opt_mask: Tensor=None, opt_lora_hook: LoraHookGroup=None, opt_timesteps: TimestepsCond=None):
(final_conditioning,) = set_mask_conds(conds=[cond_ADD],
strength=strength, set_cond_area=set_cond_area,
opt_mask=opt_mask, opt_lora_hook=opt_lora_hook, opt_timesteps=opt_timesteps)
return (final_conditioning,)