60 lines
1.8 KiB
Markdown
60 lines
1.8 KiB
Markdown
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# Documentation
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- Class name: ImageBatchRepeatInterleaving
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- Category: KJNodes/image
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- Output node: False
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ImageBatchRepeatInterleaving节点旨在通过重复批次中的每张图像指定次数来扩展图像批次。这个操作通过复制图像有效地增加了批次大小，这对于数据增强或确保统一的批处理大小非常有用。
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# Input types
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## Required
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- images
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- images参数代表要重复的图像批次。它对于定义将进行重复处理的输入数据至关重要。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- repeats
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- repeats参数指定批次中每张图像应重复的次数。它通过确定每张图像的复制因子直接影响最终的批次大小。
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- Comfy dtype: INT
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- Python dtype: int
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# Output types
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- image
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- 输出是一个新的图像批次，其中每张原始图像已根据repeats参数重复，有效地扩大了批次大小。
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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 ImageBatchRepeatInterleaving:
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "repeat"
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CATEGORY = "KJNodes/image"
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DESCRIPTION = """
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Repeats each image in a batch by the specified number of times.
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Example batch of 5 images: 0, 1 ,2, 3, 4
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with repeats 2 becomes batch of 10 images: 0, 0, 1, 1, 2, 2, 3, 3, 4, 4
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"""
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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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"repeats": ("INT", {"default": 1, "min": 1, "max": 4096}),
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},
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}
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def repeat(self, images, repeats):
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repeated_images = torch.repeat_interleave(images, repeats=repeats, dim=0)
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return (repeated_images, )
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```
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