77 lines
2.1 KiB
Markdown
77 lines
2.1 KiB
Markdown
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# Documentation
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- Class name: JWImageSaturation
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- Category: jamesWalker55
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- Output node: False
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JWImageSaturation节点用于调整输入图像的饱和度水平。通过指定的调整因子，可以增强或减弱图像颜色的强度，从而实现对图像视觉效果的精细控制。
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# Input types
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## Required
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- image
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- 需要调整饱和度的输入图像。饱和度的调整通过改变图像颜色的强度来实现。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- factor
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- 用于调整饱和度水平的乘数。当factor大于1时，会增加饱和度，使颜色更加鲜艳；当factor小于1时，会降低饱和度，使颜色变得更加柔和。
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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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- 饱和度调整后的输出图像。
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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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@register_node("JWImageMix", "Image Mix")
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class _:
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CATEGORY = "jamesWalker55"
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BLEND_TYPES = ("mix", "multiply")
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"blend_type": (cls.BLEND_TYPES, {"default": "mix"}),
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"factor": ("FLOAT", {"min": 0, "max": 1, "step": 0.01, "default": 0.5}),
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"image_a": ("IMAGE",),
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"image_b": ("IMAGE",),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "execute"
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def execute(
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self,
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blend_type: str,
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factor: float,
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image_a: torch.Tensor,
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image_b: torch.Tensor,
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):
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assert blend_type in self.BLEND_TYPES
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assert isinstance(factor, float)
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assert isinstance(image_a, torch.Tensor)
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assert isinstance(image_b, torch.Tensor)
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assert image_a.shape == image_b.shape
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if blend_type == "mix":
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mixed = image_a * (1 - factor) + image_b * factor
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elif blend_type == "multiply":
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mixed = image_a * (1 - factor + image_b * factor)
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else:
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raise NotImplementedError(f"Blend type not yet implemented: {blend_type}")
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return (mixed,)
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```
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