63 lines
1.8 KiB
Markdown
63 lines
1.8 KiB
Markdown
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# Documentation
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- Class name: DifferenceChecker
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- Category: image/filters
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- Output node: False
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DifferenceChecker 节点旨在计算两幅图像之间的绝对差异，并按指定的乘数进行缩放。这一功能对于突出显示两幅图像之间的差异或变化非常有用，可应用于各种图像处理和分析任务中。
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# Input types
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## Required
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- images1
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- 要比较的第一组图像。这个输入对于确定比较的基准至关重要。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- images2
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- 要与第一组图像进行比较的第二组图像。这个输入对于识别与基准的差异至关重要。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- multiplier
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- 应用于计算差异的缩放因子，允许调整差异的强度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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# Output types
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- image
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- 输出是一幅图像或一组图像，表示输入图像之间经过缩放的绝对差异。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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## Usage tips
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- Infra type: `GPU`
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- Common nodes: unknown
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## Source code
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```python
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class DifferenceChecker:
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def __init__(self):
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pass
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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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"images1": ("IMAGE", ),
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"images2": ("IMAGE", ),
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"multiplier": ("FLOAT", {"default": 1.0, "min": 0.01, "max": 1000.0, "step": 0.01, "round": 0.01}),
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},
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}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "difference_checker"
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CATEGORY = "image/filters"
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def difference_checker(self, images1, images2, multiplier):
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t = copy.deepcopy(images1)
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t = torch.abs(images1 - images2) * multiplier
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return (torch.clamp(t, min=0, max=1),)
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```
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