113 lines
4.6 KiB
Markdown
113 lines
4.6 KiB
Markdown
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# Documentation
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- Class name: SaltScheduleVariance
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- Category: SALT/Scheduling
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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SaltScheduleVariance节点通过将基于噪声的抖动和缓动函数结合应用于调度列表，从而创建一个变化多样的输出。这个过程通过引入受控的随机性和平滑过渡，增强了调度事件或动画的动态范围和视觉吸引力。
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# Input types
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## Required
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- schedule_list
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- 需要进行变化处理的主要调度值列表。它作为应用噪声调整和缓动函数的基础，直接影响输出的变化和动态。
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- Comfy dtype: LIST
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- Python dtype: List[float]
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## Optional
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- curves_mode
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- 指定要应用的缓动函数类型，通过平滑过渡增强调度列表。该参数允许根据特定的美学或功能需求来定制变化效果。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- use_perlin_tremors
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- 一个布尔标志，决定是否将基于噪声的抖动应用于调度列表，为变化过程引入一层受控的随机性。
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- Comfy dtype: BOOLEAN
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- Python dtype: bool
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- tremor_scale
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- 调整应用于调度列表的基于噪声的抖动强度，允许对变化效果的影响进行微调。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- octaves
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- 定义用于创建抖动的噪声层数，影响变化的复杂性和纹理。
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- Comfy dtype: INT
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- Python dtype: int
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- persistence
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- 控制噪声倍频中振幅的减少，影响抖动的平滑度和细微程度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- lacunarity
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- 决定噪声倍频中频率的增加，影响抖动的细节和尺度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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# Output types
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- schedule_list
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- 对输入调度列表应用基于噪声的抖动和缓动函数后得到的结果列表，展示了增强的变化和动态。
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- Comfy dtype: LIST
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- Python dtype: List[float]
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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 SaltScheduleVariance:
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"""
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Applies Perlin noise and optional easing curves to each value in a list to create an OPAC Schedule out of it,
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while aiming to preserve the original distribution of the input values.
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"""
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def __init__(self):
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self.noise_base = random.randint(0, 1000)
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self.perlin_noise = PerlinNoise()
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@classmethod
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def INPUT_TYPES(cls):
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easing_fn = list(easing_functions.keys())
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easing_fn.insert(0, "None")
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return {
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"required": {
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"schedule_list": ("LIST", {}),
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},
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"optional": {
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"curves_mode": (easing_fn,),
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"use_perlin_tremors": ("BOOLEAN", {"default": True}),
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"tremor_scale": ("FLOAT", {"default": 0.05, "min": 0.01, "max": 1.0}),
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"octaves": ("INT", {"default": 1, "min": 1, "max": 10}),
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"persistence": ("FLOAT", {"default": 0.5, "min": 0.01, "max": 1.0}),
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"lacunarity": ("FLOAT", {"default": 2.0, "min": 1.0, "max": 4.0}),
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}
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}
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RETURN_TYPES = ("LIST",)
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RETURN_NAMES = ("schedule_list",)
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FUNCTION = "opac_variance"
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CATEGORY = "SALT/Scheduling"
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def sample_perlin(self, frame_index, value, tremor_scale, octaves, persistence, lacunarity):
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noise = self.perlin_noise.sample(self.noise_base + frame_index * 0.1, scale=1.0, octaves=octaves, persistence=persistence, lacunarity=lacunarity)
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noise_adjustment = 1 + noise * tremor_scale
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return max(0, min(value * noise_adjustment, 1))
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def opac_variance(self, schedule_list, curves_mode="None", use_perlin_tremors=True, tremor_scale=0.05, octaves=1, persistence=0.5, lacunarity=2.0):
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self.frame_count = len(schedule_list)
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varied_list = schedule_list.copy()
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if use_perlin_tremors:
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for i, value in enumerate(schedule_list):
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noise_adjusted_value = self.sample_perlin(i, value, tremor_scale, octaves, persistence, lacunarity)
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varied_list[i] = round(noise_adjusted_value, 2)
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if curves_mode != "None" and curves_mode in easing_functions:
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for i, value in enumerate(varied_list):
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curve_adjustment = easing_functions[curves_mode](i / max(1, (self.frame_count - 1)))
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# Apply curve adjustment to the original value, not to the noise-adjusted value
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original_value_with_curve = curve_adjustment * schedule_list[i]
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# Blend the original value with curves and noise-adjusted value
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varied_list[i] = round((value + original_value_with_curve) / 2, 2)
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return (varied_list,)
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```
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