69 lines
2.5 KiB
Markdown
69 lines
2.5 KiB
Markdown
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# Documentation
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- Class name: CannyEdgePreprocessor
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- Category: ControlNet Preprocessors/Line Extractors
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- Output node: False
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CannyEdgePreprocessor节点专门用于使用Canny算法进行图像边缘检测。它通过应用Canny边缘检测器来预处理图像，突出显示图像中的边缘，使其适用于进一步的图像处理或分析任务。
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# Input types
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## Required
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- image
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- image参数是输入图像，将使用Canny算法对其进行边缘检测。
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- Comfy dtype: IMAGE
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- Python dtype: numpy.ndarray
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## Optional
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- low_threshold
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- low_threshold参数为Canny边缘检测算法中滞后阈值步骤设置下限。它有助于识别图像中的弱边缘。
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- Comfy dtype: INT
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- Python dtype: int
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- high_threshold
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- high_threshold参数为Canny边缘检测算法中滞后阈值步骤设置上限。它对于区分图像中的强边缘至关重要。
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- Comfy dtype: INT
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- Python dtype: int
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- resolution
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- resolution参数指定在应用Canny边缘检测算法之前，输入图像将被调整到的分辨率。
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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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- 输出是一张使用Canny边缘检测算法突出显示边缘的图像。
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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: `CPU`
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- Common nodes:
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- [PreviewImage](../../Comfy/Nodes/PreviewImage.md)
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- [ACN_AdvancedControlNetApply](../../ComfyUI-Advanced-ControlNet/Nodes/ACN_AdvancedControlNetApply.md)
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- [ControlNetApplyAdvanced](../../Comfy/Nodes/ControlNetApplyAdvanced.md)
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- Reroute
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- [Control Net Stacker](../../efficiency-nodes-comfyui/Nodes/Control Net Stacker.md)
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- [CR Multi-ControlNet Stack](../../ComfyUI_Comfyroll_CustomNodes/Nodes/CR Multi-ControlNet Stack.md)
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## Source code
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```python
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class Canny_Edge_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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low_threshold=("INT", {"default": 100, "min": 0, "max": 255, "step": 1}),
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high_threshold=("INT", {"default": 200, "min": 0, "max": 255, "step": 1})
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)
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "execute"
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CATEGORY = "ControlNet Preprocessors/Line Extractors"
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def execute(self, image, low_threshold, high_threshold, resolution=512, **kwargs):
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from controlnet_aux.canny import CannyDetector
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return (common_annotator_call(CannyDetector(), image, low_threshold=low_threshold, high_threshold=high_threshold, resolution=resolution), )
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```
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