55 lines
1.6 KiB
Markdown
55 lines
1.6 KiB
Markdown
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# Documentation
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- Class name: SAMPreprocessor
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- Category: ControlNet Preprocessors/others
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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SAMPreprocessor节点的设计目的是使用SAM(Segment Anything Model)方法对图像进行分割。它预处理图像以增强其效果，为进一步的处理或分析做准备，特别聚焦于分割任务。
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# Input types
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## Required
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- image
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- 需要进行分割的输入图像。这是SAMPreprocessor操作的主要数据，旨在识别和分割图像中的各种元素。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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## Optional
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- resolution
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- 指定在处理前将输入图像调整至的分辨率。此参数可能会影响分割的精度和性能。
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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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- 输出是输入图像的分割版本，其中不同的分割部分被识别和分离。
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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 SAM_Preprocessor:
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@classmethod
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def INPUT_TYPES(s):
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return create_node_input_types()
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "execute"
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CATEGORY = "ControlNet Preprocessors/others"
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def execute(self, image, resolution=512, **kwargs):
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from controlnet_aux.sam import SamDetector
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mobile_sam = SamDetector.from_pretrained().to(model_management.get_torch_device())
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out = common_annotator_call(mobile_sam, image, resolution=resolution)
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del mobile_sam
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return (out, )
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```
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