66 lines
1.7 KiB
Markdown
66 lines
1.7 KiB
Markdown
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# Documentation
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- Class name: ImageGridComposite2x2
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- Category: KJNodes/image
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- Output node: False
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ImageGridComposite2x2节点旨在将四张输入图像拼接成一个2x2的网格，有效地创建一个以视觉结构化方式组合这些输入的复合图像。
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# Input types
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## Required
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- image1
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- 第一张图像，将被放置在2x2网格的左上角。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- image2
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- 第二张图像，将被放置在2x2网格的右上角。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- image3
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- 第三张图像，将被放置在2x2网格的左下角。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- image4
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- 第四张图像，将被放置在2x2网格的右下角。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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# Output types
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- image
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- 将四张输入图像拼接成2x2网格后得到的复合图像。
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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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class ImageGridComposite2x2:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {
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"image1": ("IMAGE",),
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"image2": ("IMAGE",),
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"image3": ("IMAGE",),
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"image4": ("IMAGE",),
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}}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "compositegrid"
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CATEGORY = "KJNodes/image"
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DESCRIPTION = """
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Concatenates the 4 input images into a 2x2 grid.
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"""
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def compositegrid(self, image1, image2, image3, image4):
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top_row = torch.cat((image1, image2), dim=2)
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bottom_row = torch.cat((image3, image4), dim=2)
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grid = torch.cat((top_row, bottom_row), dim=1)
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return (grid,)
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```
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