74 lines
2.5 KiB
Markdown
74 lines
2.5 KiB
Markdown
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# Documentation
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- Class name: LeReS-DepthMapPreprocessor
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- Category: ControlNet Preprocessors/Normal and Depth Estimators
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- Output node: False
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- Repo Ref: https://github.com/comfyanonymous/ComfyUI
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LeReS深度图预处理节点旨在增强图像的深度图估计。它利用LeReS模型对图像进行预处理，提供了移除最近物体和背景的选项，以及可选的增强模式以改进深度估计。
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# Input types
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## Required
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- image
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- 需要进行深度图估计和增强的输入图像。
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- Comfy dtype: IMAGE
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- Python dtype: numpy.ndarray
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## Optional
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- rm_nearest
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- 指定从深度图中移除最近物体的阈值，有助于突出更远处的元素。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- rm_background
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- 定义深度图中背景移除的阈值，有助于突出主要主体。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- boost
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- 启用名为"boost"的增强深度估计模式，可能会提高深度图质量。
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- Comfy dtype: COMBO[STRING]
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- Python dtype: str
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- resolution
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- 指定执行深度图估计的分辨率。较高的分辨率可能会提高细节，但需要更多的计算资源。
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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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- 输出经过增强的深度图图像，可选择移除最近物体和背景，并提供增强模式以改进深度估计。
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- Comfy dtype: IMAGE
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- Python dtype: numpy.ndarray
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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 LERES_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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rm_nearest=("FLOAT", {"default": 0.0, "min": 0.0, "max": 100, "step": 0.1}),
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rm_background=("FLOAT", {"default": 0.0, "min": 0.0, "max": 100, "step": 0.1}),
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boost=(["enable", "disable"], {"default": "disable"})
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)
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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, rm_nearest, rm_background, resolution=512, **kwargs):
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from controlnet_aux.leres import LeresDetector
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model = LeresDetector.from_pretrained().to(model_management.get_torch_device())
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out = common_annotator_call(model, image, resolution=resolution, thr_a=rm_nearest, thr_b=rm_background, boost=kwargs["boost"] == "enable")
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del model
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return (out, )
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```
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