53 lines
1.4 KiB
Markdown
53 lines
1.4 KiB
Markdown
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# Documentation
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- Class name: Inference_Core_ImageGenResolutionFromLatent
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- Category: ControlNet Preprocessors
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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此节点旨在根据潜在空间表示计算图像生成分辨率。它从潜在样本中提取高度和宽度，并对其进行缩放以确定图像生成的最佳分辨率。
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# Input types
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## Required
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- latent
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- 用于推导图像生成分辨率的潜在表示。它通过确定基本维度来影响输出，这些维度将被缩放以计算最终的图像分辨率。
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- Comfy dtype: LATENT
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- Python dtype: Dict[str, torch.Tensor]
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# Output types
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- IMAGE_GEN_WIDTH (INT)
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- 输出的图像生成宽度，以像素为单位。
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- Comfy dtype: INT
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- Python dtype: int
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- IMAGE_GEN_HEIGHT (INT)
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- 输出的图像生成高度，以像素为单位。
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- Comfy dtype: INT
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- Python dtype: int
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class ImageGenResolutionFromLatent:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": { "latent": ("LATENT", ) }
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}
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RETURN_TYPES = ("INT", "INT")
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RETURN_NAMES = ("IMAGE_GEN_WIDTH (INT)", "IMAGE_GEN_HEIGHT (INT)")
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FUNCTION = "execute"
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CATEGORY = "ControlNet Preprocessors"
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def execute(self, latent):
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_, _, H, W = latent["samples"].shape
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return (W * 8, H * 8)
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```
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