76 lines
2.5 KiB
Markdown
76 lines
2.5 KiB
Markdown
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# Documentation
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- Class name: InsertImagesToBatchIndexed
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- Category: KJNodes/image
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- Output node: False
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InsertImagesToBatchIndexed 节点旨在将指定的图像插入到原始图像批次的特定位置，从而有效地通过在指定位置添加新图像来修改原始序列。这一操作允许动态操作图像批次，使得用户能够根据各种应用需求自定义图像序列。
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# Input types
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## Required
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- original_images
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- 代表将插入新图像的原始图像批次。它对于定义将被修改的基础序列至关重要。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- images_to_insert
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- 指定要插入原始批次的图像。此参数对于确定哪些新图像将被添加到序列中至关重要。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- indexes
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- 一个由逗号分隔的索引字符串，指示新图像应该插入原始批次的位置。此参数决定了图像将被添加的位置，从而影响批次的最终排列。
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- Comfy dtype: STRING
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- Python dtype: str
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# Output types
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- image
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- 在指定索引处插入新图像后的修改后的图像批次。
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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 InsertImagesToBatchIndexed:
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "insertimagesfrombatch"
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CATEGORY = "KJNodes/image"
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DESCRIPTION = """
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Inserts images at the specified indices into the original image batch.
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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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"original_images": ("IMAGE",),
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"images_to_insert": ("IMAGE",),
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"indexes": ("STRING", {"default": "0, 1, 2", "multiline": True}),
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},
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}
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def insertimagesfrombatch(self, original_images, images_to_insert, indexes):
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# Parse the indexes string into a list of integers
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index_list = [int(index.strip()) for index in indexes.split(',')]
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# Convert list of indices to a PyTorch tensor
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indices_tensor = torch.tensor(index_list, dtype=torch.long)
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# Ensure the images_to_insert is a tensor
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if not isinstance(images_to_insert, torch.Tensor):
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images_to_insert = torch.tensor(images_to_insert)
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# Insert the images at the specified indices
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for index, image in zip(indices_tensor, images_to_insert):
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original_images[index] = image
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return (original_images,)
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```
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