CavinHuang-comfyui-nodes-docs/docs/Zoe-DepthMapPreprocessor.md

Documentation

• Class name: Zoe-DepthMapPreprocessor
• Category: ControlNet Preprocessors/Normal and Depth Estimators
• Output node: False

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。

Input types

Required

• image
  • 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。
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor

Optional

• resolution
  • 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。
  • Comfy dtype: INT
  • Python dtype: int

Output types

• image
  • 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。
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes:
  • ControlNetApplyAdvanced
  • PreviewImage

Source code

class Zoe_Depth_Map_Preprocessor:
    @classmethod
    def INPUT_TYPES(s):
        return create_node_input_types()

    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "execute"

    CATEGORY = "ControlNet Preprocessors/Normal and Depth Estimators"

    def execute(self, image, resolution=512, **kwargs):
        from controlnet_aux.zoe import ZoeDetector

        model = ZoeDetector.from_pretrained().to(model_management.get_torch_device())
        out = common_annotator_call(model, image, resolution=resolution)
        del model
        return (out, )