76 lines
2.4 KiB
Markdown
76 lines
2.4 KiB
Markdown
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# Documentation
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- Class name: ImageApplyChannel
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- Category: Art Venture/Utils
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- Output node: False
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ImageApplyChannel节点旨在通过将给定的通道数据应用到图像集合的特定颜色通道（红色、绿色、蓝色、Alpha）来修改它们。这一功能允许精确控制图像的颜色组成和透明度，从而实现自定义的图像处理和操作。
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# Input types
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## Required
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- images
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- 待修改的图像集合。这个参数至关重要，因为它决定了将要进行通道修改的基础图像。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- channel_data
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- 要应用到每个图像指定通道的数据。这个参数直接影响输出结果，通过改变所有图像中指定通道的值来实现。
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- Comfy dtype: MASK
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- Python dtype: torch.Tensor
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- channel
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- 指定要在图像中修改的颜色通道（红色、绿色、蓝色、Alpha）。这个选择决定了将要改变的图像方面。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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# Output types
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- image
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- 应用了指定通道数据的修改后图像。这个输出反映了对原始图像指定通道所做的更改。
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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 UtilImageApplyChannel:
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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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"images": ("IMAGE",),
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"channel_data": ("MASK",),
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"channel": (["R", "G", "B", "A"],),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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CATEGORY = "Art Venture/Utils"
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FUNCTION = "image_apply_channel"
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def image_apply_channel(self, images: torch.Tensor, channel_data: torch.Tensor, channel):
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merged_images = []
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for image in images:
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image = image.cpu().clone()
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if channel == "A":
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if image.shape[2] < 4:
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image = torch.cat([image, torch.ones((image.shape[0], image.shape[1], 1))], dim=2)
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image[:, :, 3] = channel_data
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elif channel == "R":
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image[:, :, 0] = channel_data
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elif channel == "G":
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image[:, :, 1] = channel_data
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else:
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image[:, :, 2] = channel_data
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merged_images.append(image)
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return (torch.stack(merged_images),)
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```
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