PIA Input [Paper Presets] 🎭🅐🅓②¶
Documentation¶
- Class name:
ADE_InputPIA_PaperPresets
- Category:
Animate Diff 🎭🅐🅓/② Gen2 nodes ②/PIA
- Output node:
False
This node is designed to generate input parameters for the AnimateDiff-PIA model based on predefined paper presets. It allows users to select a preset configuration, which is then used to configure the AnimateDiff-PIA model for animation generation, providing a simplified way to apply complex animation effects.
Input types¶
Required¶
preset
- Specifies the preset configuration to use for the AnimateDiff-PIA model. Each preset corresponds to a predefined set of parameters that define specific animation effects.
- Comfy dtype:
COMBO[STRING]
- Python dtype:
str
batch_index
- Determines the index of the batch for which the input is being generated. This is used to manage multiple animation inputs within a batch processing context.
- Comfy dtype:
INT
- Python dtype:
int
Optional¶
mult_multival
- An optional multiplier that can be applied to multiple values within the preset, allowing for further customization of the animation effect.
- Comfy dtype:
MULTIVAL
- Python dtype:
Union[float, torch.Tensor]
print_values
- When set to True, the selected preset's parameters are logged, providing insight into the specific configuration being applied.
- Comfy dtype:
BOOLEAN
- Python dtype:
bool
Output types¶
pia_input
- Comfy dtype:
PIA_INPUT
- Generates a configured input for the AnimateDiff-PIA model based on the selected paper preset.
- Python dtype:
InputPIA
- Comfy dtype:
Usage tips¶
- Infra type:
CPU
- Common nodes: unknown
Source code¶
class InputPIA_PaperPresetsNode:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"preset": (PIA_RANGES._LIST_ALL,),
"batch_index": ("INT", {"default": 0, "min": BIGMIN, "max": BIGMAX, "step": 1}),
},
"optional": {
"mult_multival": ("MULTIVAL",),
"print_values": ("BOOLEAN", {"default": False},),
#"effect_multival": ("MULTIVAL",),
}
}
RETURN_TYPES = ("PIA_INPUT",)
CATEGORY = "Animate Diff 🎭🅐🅓/② Gen2 nodes ②/PIA"
FUNCTION = "create_pia_input"
def create_pia_input(self, preset: str, batch_index: int, mult_multival: Union[float, Tensor]=None, print_values: bool=False, effect_multival: Union[float, Tensor]=None):
# verify preset exists - function will throw error if does not
values = PIA_RANGES.get_preset(preset)
if print_values:
logger.info(f"PIA Preset '{preset}': {values}")
return (InputPIA_PaperPresets(preset=preset, index=batch_index, mult_multival=mult_multival, effect_multival=effect_multival),)