feat: copy docs

2024-07-04 08:39:03 +08:00
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+
+# Documentation
+- Class name: Inference_Core_PiDiNetPreprocessor
+- Category: ControlNet Preprocessors/Line Extractors
+- Output node: False
+
+PiDiNet预处理器节点旨在预处理图像以提取软边缘线条，利用PiDiNet模型实现增强线条检测。它支持可配置的安全模式和分辨率设置，以适应各种图像处理需求。
+
+# Input types
+## Required
+- image
+    - 需要进行线条提取处理的输入图像。这是PiDiNet模型操作的主要数据。
+    - Comfy dtype: IMAGE
+    - Python dtype: torch.Tensor
+## Optional
+- safe
+    - 一种启用或禁用图像处理过程中安全检查的模式，影响执行路径并可能影响输出质量。
+    - Comfy dtype: COMBO[STRING]
+    - Python dtype: str
+- resolution
+    - 处理前将输入图像调整到的分辨率，影响提取线条的细节水平。
+    - Comfy dtype: INT
+    - Python dtype: int
+
+# Output types
+- image
+    - 经过处理的图像，展示了提取的线条，突显了PiDiNet模型在增强线条检测方面的能力。
+    - Comfy dtype: IMAGE
+    - Python dtype: torch.Tensor
+
+
+## Usage tips
+- Infra type: `GPU`
+- Common nodes: unknown
+
+
+## Source code
+```python
+class PIDINET_Preprocessor:
+    @classmethod
+    def INPUT_TYPES(s):
+        return create_node_input_types(
+            safe=(["enable", "disable"], {"default": "enable"})
+        )
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "execute"
+
+    CATEGORY = "ControlNet Preprocessors/Line Extractors"
+
+    def execute(self, image, safe, resolution=512, **kwargs):
+        from controlnet_aux.pidi import PidiNetDetector
+
+        model = PidiNetDetector.from_pretrained().to(model_management.get_torch_device())
+        out = common_annotator_call(model, image, resolution=resolution, safe = safe == "enable")
+        del model
+        return (out, )
+
+```