55 lines
1.5 KiB
Markdown
55 lines
1.5 KiB
Markdown
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# Documentation
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- Class name: BAE-NormalMapPreprocessor
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- Category: ControlNet Preprocessors/Normal and Depth Estimators
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- Output node: False
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BAE-NormalMapPreprocessor节点旨在使用BAE (Boundary Aware Encoder) 模型对图像进行预处理以生成法线图。它通过估算表面法线来增强图像，为进一步处理或可视化做准备。
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# Input types
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## Required
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- image
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- 需要处理以生成法线图的输入图像。
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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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- 处理前将输入图像调整到的分辨率。这会影响生成的法线图的细节水平。
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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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- 从输入图像生成的输出法线图，提供表面法线的估计。
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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 BAE_Normal_Map_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/Normal and Depth Estimators"
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def execute(self, image, resolution=512, **kwargs):
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from controlnet_aux.normalbae import NormalBaeDetector
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model = NormalBaeDetector.from_pretrained().to(model_management.get_torch_device())
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out = common_annotator_call(model, image, resolution=resolution)
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del model
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return (out,)
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```
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