58 lines
1.8 KiB
Markdown
58 lines
1.8 KiB
Markdown
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# Documentation
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- Class name: Zoe-DepthMapPreprocessor
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- Category: ControlNet Preprocessors/Normal and Depth Estimators
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- Output node: False
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Zoe-DepthMapPreprocessor节点用于利用Zoe Detector模型对图像进行深度图估计的预处理。它会调整输入图像的分辨率，并通过模型处理以生成深度图。生成的深度图可用于3D建模和场景理解等多种应用。
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# Input types
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## Required
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- image
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- 用于深度图估计的输入图像。这是Zoe Detector模型分析并生成相应深度图的主要输入。
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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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- 指定处理前将输入图像调整至的分辨率。此参数允许标准化输入大小，以便在不同图像间进行一致的深度图估计。
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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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- 从输入图像生成的深度图。这个深度图提供了每个像素的深度估计，有助于理解场景的空间布局。
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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:
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- [ControlNetApplyAdvanced](../../Comfy/Nodes/ControlNetApplyAdvanced.md)
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- [PreviewImage](../../Comfy/Nodes/PreviewImage.md)
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## Source code
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```python
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class Zoe_Depth_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.zoe import ZoeDetector
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model = ZoeDetector.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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