86 lines
3.6 KiB
Markdown
86 lines
3.6 KiB
Markdown
# AnimateDiff+CameraCtrl Keyframe 🎭🅐🅓
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## Documentation
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- Class name: ADE_CameraCtrlAnimateDiffKeyframe
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- Category: Animate Diff 🎭🅐🅓/② Gen2 nodes ②/CameraCtrl
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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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此节点旨在生成和管理包含摄像机控制的动画关键帧，从而在AnimateDiff框架内创建动态和复杂的摄像机运动。它允许指定动画的起始百分比，应用多值进行缩放、效果和摄像机控制，并继承缺失值以确保关键帧之间的连续性。
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## Input types
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### Required
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- start_percent
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- 指定动画的起始百分比，允许精确控制动画中摄像机运动和效果的时间。
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- Comfy dtype: FLOAT
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- Python dtype: float
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### Optional
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- prev_ad_keyframes
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- 可选。允许包括先前定义的AnimateDiff关键帧，使动画可以进行更复杂的序列链和层叠。
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- Comfy dtype: AD_KEYFRAMES
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- Python dtype: ADKeyframeGroup or None
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- scale_multival
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- 可选。应用缩放因子到动画，允许调整动画元素的大小。
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- Comfy dtype: MULTIVAL
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- Python dtype: float or torch.Tensor
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- effect_multival
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- 可选。应用各种效果到动画，允许添加视觉增强或修改。
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- Comfy dtype: MULTIVAL
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- Python dtype: float or torch.Tensor
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- cameractrl_multival
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- 可选。指定摄像机控制的多个值，允许在动画中创建复杂的摄像机运动。
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- Comfy dtype: MULTIVAL
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- Python dtype: float or torch.Tensor
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- inherit_missing
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- 确定当前关键帧中的缺失值是否应继承自前面的关键帧，以确保动画的连续性。
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- Comfy dtype: BOOLEAN
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- Python dtype: bool
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- guarantee_steps
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- 指定动画中保证的最小步数，确保一定程度的平滑和连续性。
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- Comfy dtype: INT
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- Python dtype: int
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## Output types
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- ad_keyframes
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- Comfy dtype: AD_KEYFRAMES
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- 生成一系列AnimateDiff关键帧，使动画具有复杂的摄像机运动。
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- Python dtype: ADKeyframeGroup
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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 CameraCtrlADKeyframeNode:
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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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"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}, ),
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},
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"optional": {
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"prev_ad_keyframes": ("AD_KEYFRAMES", ),
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"scale_multival": ("MULTIVAL",),
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"effect_multival": ("MULTIVAL",),
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"cameractrl_multival": ("MULTIVAL",),
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"inherit_missing": ("BOOLEAN", {"default": True}, ),
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"guarantee_steps": ("INT", {"default": 1, "min": 0, "max": BIGMAX}),
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}
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}
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RETURN_TYPES = ("AD_KEYFRAMES", )
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FUNCTION = "load_keyframe"
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CATEGORY = "Animate Diff 🎭🅐🅓/② Gen2 nodes ②/CameraCtrl"
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def load_keyframe(self,
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start_percent: float, prev_ad_keyframes=None,
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scale_multival: Union[float, torch.Tensor]=None, effect_multival: Union[float, torch.Tensor]=None,
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cameractrl_multival: Union[float, torch.Tensor]=None,
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inherit_missing: bool=True, guarantee_steps: int=1):
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return ADKeyframeNode.load_keyframe(self,
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start_percent=start_percent, prev_ad_keyframes=prev_ad_keyframes,
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scale_multival=scale_multival, effect_multival=effect_multival, cameractrl_multival=cameractrl_multival,
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inherit_missing=inherit_missing, guarantee_steps=guarantee_steps
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) |