[Inference.Core] Standard Lineart

Documentation

• Class name: Inference_Core_LineartStandardPreprocessor
• Category: ControlNet Preprocessors/Line Extractors
• Output node: False

The Inference_Core_LineartStandardPreprocessor node is designed to preprocess images for line extraction, applying Gaussian blurring and intensity thresholding to enhance lineart features before further processing.

Input types

Required

• image
  • The input image to be processed for line extraction, serving as the primary data for the node's operations.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor

Optional

• guassian_sigma
  • unknown
  • Comfy dtype: FLOAT
  • Python dtype: unknown
• intensity_threshold
  • Determines the threshold for intensity differentiation, aiding in the distinction of lineart from the background by setting a cutoff intensity value.
  • Comfy dtype: INT
  • Python dtype: int
• resolution
  • Specifies the resolution at which the image processing should be executed, affecting the detail level of the output lineart.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• image
  • Comfy dtype: IMAGE
  • Produces an image with enhanced lineart features, ready for further processing or analysis.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: GPU
• Common nodes: unknown

Source code

class Lineart_Standard_Preprocessor:
    @classmethod
    def INPUT_TYPES(s):
        return create_node_input_types(
            guassian_sigma=("FLOAT", {"default": 6.0, "min": 0.0, "max": 100.0}),
            intensity_threshold=("INT", {"default": 8, "min": 0, "max": 16})
        )

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

    CATEGORY = "ControlNet Preprocessors/Line Extractors"

    def execute(self, image, guassian_sigma, intensity_threshold, resolution=512, **kwargs):
        from controlnet_aux.lineart_standard import LineartStandardDetector
        return (common_annotator_call(LineartStandardDetector(), image, guassian_sigma=guassian_sigma, intensity_threshold=intensity_threshold, resolution=resolution), )