66 lines
1.8 KiB
Markdown
66 lines
1.8 KiB
Markdown
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# Documentation
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- Class name: GetImagesFromBatchIndexed
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- Category: KJNodes/image
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- Output node: False
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GetImagesFromBatchIndexed节点旨在根据指定的索引从给定的图像批次中选择性地检索图像，有效地创建一个仅包含给定位置图像的新批次。
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# Input types
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## Required
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- images
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- 要从中选择图像的批次。索引决定了哪些图像将被包含在输出批次中。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- indexes
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- 指定要从批次中选择的图像索引的字符串。这允许灵活地选择图像。
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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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- 返回指定索引处选择的图像，作为一个新的批次。
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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 GetImagesFromBatchIndexed:
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "indexedimagesfrombatch"
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CATEGORY = "KJNodes/image"
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DESCRIPTION = """
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Selects and returns the images at the specified indices as an 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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"images": ("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 indexedimagesfrombatch(self, images, 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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# Select the images at the specified indices
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chosen_images = images[indices_tensor]
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return (chosen_images,)
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```
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